Quantization

Two-dimensional quantum-mechanical simulations of nonoverlapped MOS devices are presented, and validated through comparison against experimental data. Simulations are used to highlight the electrical characteristics of these devices, explore their design tradeoffs and optimize the performance with respect to the nonoverlap length. Simulations show that a minimum switching time is always achieved by adopting a nonoverlapped structure if the MOS device is operating properly. This approach can effectively improve the performance of decananometer MOSFETs. Index Terms-MOS devices, quantization, semiconductor device modeling, source/drain (S/D) overlap.

The aim of the present study was to determine the diagnostic accuracy of 64-slice computed tomography (CT) to identify and quantify atherosclerotic coronary lesions in comparison with catheter-based angiography and intravascular ultrasound (IVUS). BACKGROUND Currently, the ability of multislice CT to quantify the degree of coronary artery stenosis and dimensions of coronary plaques has not been evaluated.

We investigate the properties of a control law which quantizes the unconstrained solution to a unitary horizon quadratic programme. From a quantized receding horizon point of view, this naïve quantized control law is globally optimal for horizon one. However, the question arises as to whether it is also globally optimal for horizons greater than one, i.e. whether it solves (in a receding horizon sense) a multi-step quadratic programme, where decision variables are restricted to belong to a quantized set. By using dynamic programming, we develop necessary and sufficient conditions for this to hold for the case of first order plants. The results can be applied to arbitrary horizons and quantized sets, which may contain a finite or an infinite (though countable) number of elements.

Digital baseband predistortion is a well known technique to compensate for AM/AM and AM/PM amplifier non linearity. The practical implementation of a flexible digital predistorter suggests introducing some adaptation strategy to the predistortion technique in order to take count of the changes in the non linear characteristics due to ageing, temperature or channel switching of the amplifier. The most effective adaptation criterions are generally based on the estimation of the residual non linear distortion at the output of the predistorted amplifier. A simple criterion is to compare the amplifier output with the predistorter input. This comparison requires an estimation of the input-output time delay of the amplification chain. Aim of this work is to analyse the sensitivity of the adaptation algorithm to errors in the time delay estimation and to noise sources like quantization and inter symbol interference.

We introduce a new class of multiple description scalar quantizer (MDSQ), which will be referred to as the modified MDSQ (MMDSQ). The structure of MMDSQ is fundamentally different from the MDSQ proposed by Vaishampayan. Analysis shows that at high rates for sources with smooth pdfs, MMDSQ achieves the same performance as entropy-constrained MDSQ using a uniform central quantizer. Compared with MDSQ, MMDSQ features a more efficient central-side distortion tradeoff control mechanism, without requiring the design and implementation of a complicated index assignment scheme. The simple and efficient implementation of MMDSQ makes it suitable for image coding: It can be naturally incorporated into existing coders to form new multiple description coders. Such a system is constructed using an existing image coder, and the performance of the resulting system is compared to that of the same coder but using Vaishampayan's MDSQ. Simulation results on natural images reveal that the system based on MMDSQ outperforms that based on MDSQ.

The effect of adding dither to a given signal before its quantization is investigated. To this aim the relationship between the statistical description of the dither and the mean value of the quantization error and of the quantizer output is derived. The presented results allow the determination of the resolution limits that can be achieved by low-pass filtering a set of quantized samples of a slowly varying dithered signal. Discrete, uniform, sinusoidal, and Gaussian dithering are analyzed, thus providing a quantitative basis for choosing the most appropriate dither signal for a given application.

In this paper, the Cramér-Rao Lower Bound (CRLB) for the parametric estimation of quantized sinewaves is analyzed, including the effect of analog-to-digital-converter (ADC) noise. An accurate model based on the statistical properties of quantized data is presented, which takes into account both the effects of the finite ADC resolution and of the quantizer overloading phenomena at a low computational cost. Then, the model is validated by comparing the obtained results with the CRLB based on the ADC uniform noise model.

Spectral leakage is a well-known phenomenon induced by the windowing process and usually revealed in the frequency domain. Scientific literature has deeply investigated the spectral leakage of narrow-band components. However, the problem of windowing a wide-band colored noise has not yet been fully characterized. In this paper, the effect of the windowing process on the estimate of the in-band ∆Σ-shaped quantizationnoise power spectral density is investigated. The reported analysis holds for any modulator order and for any kind of real and symmetric window and proves the necessity of the windowing process in order to reduce the in-band noise power estimation bias. Moreover, an a priori criterion for designing the optimal window that reduces the shaped-noise spectral leakage and for choosing the minimum number of acquired samples to be employed is derived.

A novel frequency-domain technique for image blocking artifact detection and reduction is presented in this paper. The algorithm first detects the regions of the image which present visible blocking artifacts. This detection is performed in the frequency domain and uses the estimated relative quantization error calculated when the discrete cosine transform (DCT) coefficients are modeled by a Laplacian probability function. Then, for each block affected by blocking artifacts, its dc and ac coefficients are recalculated for artifact reduction. To achieve this, a closed-form representation of the optimal correction of the DCT coefficients is produced by minimizing a novel enhanced form of the mean squared difference of slope for every frequency separately. This correction of each DCT coefficient depends on the eight neighboring coefficients in the subband-like representation of the DCT transform and is constrained by the quantization upper and lower bound. Experimental results illustrating the performance of the proposed method are presented and evaluated.

This paper investigates the application of a mixed synchronous/asynchronous digital controller to dc-dc boost converters. The digital control synchronously generates current and voltage ramps by using two low-resolution Digital-to-Analog Converters (DACs). Switch turn-on and turn-off are determined asynchronously by comparing converter state variables and the digitally generated current and voltage ramps. The control features high dynamic performance, frequency modulation during transients, no quantization effects, and low-complexity. In order to evaluate the dynamic performance and to compare the proposed solution with conventional analog peak current-mode control, a small signal model of the synchronous/asynchronous modulation is derived. Even if aimed to an integrated digital controller, experimental investigation has been performed using discrete components, implementing the digital control in a Field Programmable Gate Array (FPGA) using a hardware description language (VHDL). Simulation and experimental results on 100 W dc-dc boost converter confirm the proposed analysis and shows that the proposed solution enables dynamic performance comparable to that of analog peak current-mode control.

Crosstalk interference is the limiting factor in transmiss ion over copper lines. Crosstalk cancelation techniques show great potential for enabling the next leap in DSL transmission rates. An important issue when implementing crosstalk cancelation techniques in hardware is the effect of finite world length on performance. In this paper we provide an analysis of the performance of linear zero-forcing precoders,

Bandstructure effects in PMOS transport of strongly quantized silicon nanowire field-effect-transistors (FET) in various transport orientations are examined. A 20-band sp 3 d 5 s* spin-orbit-coupled (SO) atomistic tight-binding model coupled to a self consistent Poisson solver is used for the valence band dispersion calculation. A ballistic FET model is used to evaluate the capacitance and current-voltage characteristics. The dispersion shapes and curvatures are strong functions of device size, lattice orientation, and bias, and cannot be described within the effective mass approximation. The anisotropy of the confinement mass in the different quantization directions can cause the charge to preferably accumulate in the (110) and secondly on the (112) rather than (100) surfaces, leading to significant charge distributions for different wire orientations. The total gate capacitance of the nanowire FET devices is, however, very similar for all wires in all the transport orientations investigated ([100], [110], [111]), and is degraded from the oxide capacitance by ~30%. The [111] and secondly the [110] oriented nanowires indicate highest carrier velocities and better ON-current performance compared to [100] wires.

We describe a trellis-based algorithm which enables R-D optimum quantization decisions in the H.263+ video coding standard. The algorithm allows the quantization decisions for all coefficients in a block to be made jointly, and experiments conducted using H.263+ for video coding rates of 40-50 kbps show an average improvement of 3.5% in bitrate relative to implementations which follow the International Telecommunications Union (ITU) Test Model specifications in making quantization decisions. Index Terms-Dynamic programming, H.263+, R-D optimization, video coding.

We present a new technique for sharpening compressed images in the discrete-cosine-transform domain. For images compressed using the JPEG standard, image sharpening is achieved by suitably scaling each element of the encoding quantization table to enhance the high-frequency characteristics of the image. The modified version of the encoding table is then transmitted in lieu of the original. Experimental results with scanned images show improved text and image quality with no additional computation cost and without affecting compressibility.

Let there be M hypotheses H 1 ,... , HM, and let Y be a random variable, taking values in a set y, with different probability distribution under each hypothesis. A quantizer -': Y-+ {1,..., D} is applied to form a quantized random variable 7(Y). We characterize the extreme points of the set of possible probability distributions of -(Y), as 7y ranges over all quantizers. We then establish optimality properties of likelihood-ratio quantizers for a very broad class of quantization problems, including problems involving the maximization of an Ali-Silvey distance measure. Some new results are also obtained for a Neyman-Pearson decentralized detection problem.

This paper develops a new class of algorithms for signal recovery in the distributed compressive sensing (DCS) framework. DCS exploits both intra-signal and inter-signal correlations through the concept of joint sparsity to further reduce the number of measurements required for recovery. DCS is wellsuited for sensor network applications due to its universality, computational asymmetry, tolerance to quantization and noise, and robustness to measurement loss. In this paper we propose recovery algorithms for the sparse common and innovation joint sparsity model. Our approach leads to a class of efficient algorithms, the Texas Hold 'Em algorithms, which are scalable both in terms of communication bandwidth and computational complexity.

Quantization noise shaping is commonly used in oversampled A/D and D/A converters with uniform sampling. This paper considers quantization noise shaping for arbitrary finite frame expansions based on generalizing the view of first-order classical oversampled noise shaping as a compensation of the quantization error through projections. Two levels of generalization are developed, one a special case of the other, and two different cost models are proposed to evaluate the quantizer structures. Within our framework, the synthesis frame vectors are assumed given, and the computational complexity is in the initial determination of frame vector ordering, carried out off-line as part of the quantizer design. We consider the extension of the results to infinite shift-invariant frames and consider in particular filtering and oversampled filter banks.

We come up with a class of distributed quantized averaging algorithms on asynchronous communication networks with fixed, switching and random topologies. The implementation of these algorithms is subject to the realistic constraint that the communication rate, the memory capacities of agents and the computation precision are finite. The focus of this paper is on the study of the convergence time of the proposed quantized averaging algorithms. By appealing to random walks on graphs, we derive polynomial bounds on the expected convergence time of the algorithms presented. February 10, 2010 DRAFT indivisible tasks. Prior work on distributed quantized averaging over fixed graphs includes [1], [6], [7], [11]. Recently, [13] examines quantization effects on distributed averaging algorithms over time-varying topologies. As in [11], we focus on quantized averaging algorithms preserving the sum of the state values at each iteration. This setup has the following properties of interest:

Compaction methods have been successively used for off-line testing of both digital and analog circuits as well as on-line (concurrent) testing of digital circuits. In this work, we extend the use of compaction methods for concurrent testing of analog-to-digital converters. We estimate tolerance bounds for the result of compaction and evaluate the aliasing rate.

We study the problem of quantized consensus where some agents are subject to faults and attacks and might make updates arbitrarily. The network consists of integer-valued agents under directed communication links. The misbehaving agents are assumed to be omniscient and may try to prevent the normal agents to reach consensus. We show that consensus can be achieved among the normal agents via a simple update scheme under which each normal agent ignores some of its neighbors' states taking unsafe values. We employ the connectivity notion of graph robustness and provide necessary and sufficient conditions for resilient consensus in a network with a known bounded number of faulty agents. It will be shown that randomization is essential both in quantization and in the updating times when normal agents interact in an asynchronous manner.

Chiral antisymmetric tensor fields can have chiral couplings to quarks and leptons. Their kinetic terms do not mix different representations of the Lorentz symmetry and a local mass term is forbidden by symmetry. The chiral couplings to the fermions are asymptotically free, opening interesting perspectives for a possible solution to the gauge hierarchy problem. We argue that the interacting theory for such fields can be consistently quantized, in contrast to the free theory which is plagued by unstable solutions. We suggest that at the scale where the chiral couplings grow large the electroweak symmetry is spontaneously broken and a mass term for the chiral tensors is generated non-perturbatively. Massive chiral tensors correspond to massive spin one particles that do not have problems of stability. We also propose an equivalent formulation in terms of gauge fields.

We consider sigma-delta quantization of Cyclic Geometrically Uniform (CGU) nites frames, family of frames containing nite harmonic frames (both in C M and R M ). For rst-and second-order sigma-delta quantizers, we establish that the reconstruction minimum squares error (MSE) behaves as 1 r 2 where r denotes the frame redundancy. This result is shown to be true both under the quantization model used in as well as under the widely used additive white quantization noise assumption. For the widely used L-th order noise shaping lter G(z) = (1 − z −1 ) L , we show that the MSE behaves as 1 r 2 irrespectively of the lter order L. More importantly, we prove also that in the case of tight and normalized CGU frame, when the frame length is too large compared to the lter order, the reconstruction MSE can decay as faster as O( 1 r 2L+1 ).

In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems.

Puri and Aravind's method of macroblock bit count estimation for video rate control is based on the classification of the macroblock data into discrete classes and assigning a unique nonlinear estimate for each class and quantization parameter pair. This method stands apart from other methods in the literature, since the model of the bit count versus the quantization parameter relation, parameterized by macroblock variance, is a discrete model generated solely from measurements. We extend their technique for lowdelay video rate control (tight buffer regulation) in two ways. We propose a strategy of near-uniform quantization parameter assignments to the macroblocks of a frame that can come close to maximizing an objective spatial quality function, such as PSNR, over the entire frame. We also adaptively update the quantization parameter assignments for the yet to be coded macroblocks, after the encoding of each macroblock, to compensate for any errors in the bit count estimation of the encoded macroblock. Our experiments demonstrate that the proposed rate control method can more accurately control the number of bits expended for a frame, as well as yield a higher objective spatial quality than the method adopted by TMN8.

Compressive sensing is a new data acquisition technique that aims to measure sparse and compressible signals at close to their intrinsic information rate rather than their Nyquist rate. Recent results in compressive sensing show that a sparse or compressible signal can be reconstructed from very few measurements with an incoherent, and even randomly generated, dictionary. To date the hardware implementation of compressive sensing analog-todigital systems has not been straightforward. This paper explores the use of Sigma-Delta quantizer architecture to implement such a system. After examining the challenges of using Sigma-Delta with a randomly generated compressive sensing dictionary, we present efficient algorithms to compute the coefficients of the feedback loop. The experimental results demonstrate that Sigma-Delta relaxes the required analog filter order and quantizer precision. We further demonstrate that restrictions on the feedback coefficient values and stability constraints impose a small penalty on the performance of the Sigma-Delta loop, while they make hardware implementations significantly simpler.

Abstract Variable size matrix segmentation and variable size transform are used in the colour image compression methods based on three dimensional matrix widely discrete cosine transform (3DMWDCT). However the coefficients have different statistical properties since different areas of an image and difference size blocks have difference energy centralization. 3D balance quantization based human visual system was proposed in this paper. After dividing the original colour image into variable sized sub-three dimensional ...

We discuss the relevance to deformation quantization of Feichtinger's modulation spaces, especially of the weighted Sjoestrand classes. These function spaces are good classes of symbols of pseudo-differential operators (observables). They have a widespread use in time-frequency analysis and related topics, but are not very well-known in physics. It turns out that they are particularly well adapted to the study of the Moyal star-product and of the star-exponential.

This paper presents an overview of the developments made in the field of oversampling sigma-delta (SigmaDelta) data converters. Further, an approach to model a 4th order multi-bit SigmaDelta ADC using Simulink, Matlab is proposed. It is shown that behavioral modeling provides comparable accurate results, and is much faster in comparison to spectre based simulations.

Object recognition has made great strides recently. However, the best methods, such as those based on kernel-SVMs are highly computationally intensive. The problem of how to accelerate the evaluation process without decreasing accuracy is thus of current interest. In this paper, we deal with this problem by using the idea of ranking. We propose a cascaded architecture which using the ranking SVM generates an ordered set of proposals for windows containing object instances. The top ranking windows may then be fed to a more complex detector. Our experiments demonstrate that our approach is robust, achieving higher overlap-recall values using fewer output proposals than the state-of-the-art. Our use of simple gradient features and linear convolution indicates that our method is also faster than the state-of-the-art.

Abstracr -It is known that numerical performance of a discrete filter is strictly dependant to the state space realization adopted In particular realization matrix plays an important role into determination of a good representation when a finite length arithmetic is used. The optimal representation problem has not in general a solution in closed-form and numerical optimization algorithms must be adopted. Genetic Algorithms, a new class of optimization procedure that simulate natural adaptation, have shown to be a valid alternative respect to a classical approach. This procedure allows to find near-optimal solution by avoiding to deep in local minima.

LDPC codes are state-of-art error correcting codes, included in several standards for broadcast transmissions. Iterative soft-decision decoding algorithms for LDPC codes reach excellent error correction capability; their performance, however, is strongly affected by finite-precision issues in the representation of inner variables. Great attention has been paid, in recent literature, to the topic of quantization for LDPC decoders, but mostly focusing on binary modulations and analysing finite precision effects in a disaggregrated manner, i.e., considering separately each block of the receiver. Modern telecommunication standards, instead, often adopt high order modulation schemes, e.g. M-QAM, with the aim to achieve large spectral efficiency. This puts additional quantization problems, that have been poorly debated in previous literature. This paper discusses the choice of suitable quantization characteristics for both the decoder messages and the received samples in LDPC-coded systems using M-QAM schemes. The analysis involves also the demapper block, that provides initial likelihood values for the decoder, by relating its quantization strategy with that of the decoder. A new demapper version, based on approximate expressions, is also presented, that introduces a slight deviation from the ideal case but yields a low complexity hardware implementation.

We investigate the effect of non idealities in the diagonalizing precoder vectoring technique used for cancellation of the far-end crosstalk in downstream VDSL networks. The contribution of the paper is twofold: on one hand we provide analytical formulas to estimate the average bit rates achievable as a function of both relative and absolute estimation errors; on the other hand we show that, by adopting a smart quantization law, the number of quantization bits required for not exceeding a given transmission rate loss can be smaller than that foreseen by previous analyses.

Presence of depth and compression artifacts have been identified as major factors that influence subjective quality of experience and satisfaction of 3D imagery visualized on a portable auto-stereoscopic display. The juxtaposition between these two factors has been investigated through psychometric subjective experiment, where participants have evaluated the overall quality of stereoscopic images with varying both presences of depth and compression levels. The results reveal that compression artifacts dominate the quality of experience compared to varying depth range.

Purpose: To develop an ex vivo human carotid artery stenting model that can be used for the quantitative analysis of risk for embolization associated with balloon angioplasty and stenting and to correlate this risk with lesion characteristics to define lesions suitable for balloon angioplasty and stenting. Methods: Specimens of carotid plaque (n = 24) were obtained circumferentially intact from patients undergoing standard carotid endarterectomy. Carotid lesions were prospectively characterized on the basis of angiographic and duplex findings before endarterectomy and clinical findings. Specimens were encased in a polytetrafluoroethylene wrap and mounted in a flow chamber that allowed access for endovascular procedures and observations. Balloon angioplasty and stenting were performed under fluoroscopic guidance with either a Palmaz stent or a Wallstent endoprosthesis. Ex vivo angiograms were obtained before and after intervention. Effluent from each specimen was filtered for released embolic particles, which were microscopically examined, counted, and correlated with various plaque characteristics by means of multivariate analysis. Results: Balloon angioplasty and stenting produced embolic particles that consisted of atherosclerotic debris, organized thrombus, and calcified material. The number of embolic particles detected after balloon angioplasty and stenting was not related to preoperative symptoms, sex, plaque ulceration or calcification, or artery size. However, echolucent plaques generated a higher number of particles compared with echogenic plaques (p < 0.01). In addition, increased lesion stenosis also significantly correlated with the total number of particles produced by balloon angioplasty and stenting (r = 0.55). Multivariate analysis revealed that these two characteristics were independent risk factors. Conclusions: Echolucent plaques and plaques with stenosis ≥90% produced a higher number of embolic particles and therefore may be less suitable for balloon angioplasty and stenting. This ex vivo model can be used to identify high-risk lesions for balloon angioplasty and stenting and can aid in the evaluation of new devices being considered for carotid balloon angioplasty and stenting. (J Vasc Surg 1998; 27:463-71)

Distributed coding of correlated sources with memory poses a number of considerable challenges that threaten its practical application, particularly (but not only) in the context of sensor networks. This problem is strongly motivated by the obvious observation that most common sources exhibit temporal correlations that may be at least as important as spatial or intersource correlations. This paper presents an analysis of the underlying tradeoffs, paradigms for coding systems, and approaches for distributed predictive coder design optimization. Motivated by practical limitations on both complexity and delay (especially for dense sensor networks) the focus here is on predictive coding. From the source coding perspective, the most basic tradeoff (and difficulty) is due to conflicts that arise between distributed coding and prediction, wherein "standard" distributed quantization of the prediction errors, if coupled with imposition of zero decoder drift, would drastically compromise the predictor performance and hence the ability to exploit temporal correlations. Another challenge arises from instabilities in the design of closed-loop predictors, whose impact has been observed in the past, but is greatly exacerbated in the case of distributed coding. In the distributed predictive coder design, we highlight the fundamental tradeoffs encountered within a more general paradigm where decoder drift is allowable or unavoidable, and must be effectively accounted for and controlled. We derive an overall design optimization method for distributed predictive coding that avoids the pitfalls of naive distributed predictive quantization and produces an optimized low complexity and low delay coding system. The proposed iterative algorithms for distributed predictive coding subsume traditional single-source predictive coding and memoryless distributed coding as extreme special cases.

Most studies using X-chromosome inactivation patterns (XCIPs) to determine clonality in females have used polymorphic DNA loci, but interpretation may be complicated by the complexity of the differential methylation patterns necessary to distinguish active and inactive X-chromosomes. Recent description of polymorphisms within the transcribed region of three X-chromosome genes has enabled XCIP analysis of allele expression at the RNA level, which should circumvent this problem. We report here a quantitative RT-PCR assay for one of these loci, the iduronate-2-sulphatase (IDS) gene, using a mismatch primer to introduce a BclI cutting site in one of the alleles. DNA samples from 150 females were screened and 61 (41%) were found to be informative for the polymorphism. Reproducible results were obtained from clonal analysis of 56 RNA samples covering the complete spectrum of XCIP ratios. The values correlated closely with those obtained from the corresponding DNA samples analyzed using either PGK or HUM-ARA (r = 0.98) provided that the number of amplification cycles was limited to 25 to reduce heteroduplex formation. However, sample purity is of greater importance than in the DNA-based assays as contaminating red cells and platelets will still contain the relevant transcripts and could influence the result.

A low-power quadrature direct digital frequency synthesizer (DDFS) is presented. Piecewise linear approximation is used to avoid using ROM lookup table to store the sine values. ROM elimination has resulted in significant power and area savings. The proposed DDFS has been implemented using 0.5µm CMOS process and occupies 1.4mm 2 area. It achieves an extremely low power consumption of only 8mW at 100M Hz and operates from a single 2.7V supply. The SFDR is better than 58dBc at low synthesized frequencies and the frequency resolution is 1.5kHz.

Fungal spores constitute a sizeable fraction of coarse organic carbon (OC) in the atmospheric aerosol. In order to avoid tedious spore count methods, tracers for quantifying the spore-OC in atmospheric aerosol are sought. Arabitol and mannitol have been proposed as such tracers, since no other emission sources for these compounds have been reported. By parallel investigations of spore counts and tracer determinations from PM 10 filter samples we could derive quantitative relationships between the amounts of tracer compounds and the numbers of spores in the atmosphere for different sites in the area of Vienna. We obtained over all average relationships of 1.2 pg arabitol spore À1 , with a range of 0.8-1.8, and 1.7 pg mannitol spore À1 , with a range of 1.2-2.4, with a clear site dependence. Thus, using these conversion factors from spore counts to spore-OC and spore-mass, along with analytical data for arabitol or mannitol in filter samples, the contribution of fungal spores to the OC and to the mass balance of atmospheric aerosol particles can be estimated. r

The performance of quantization-based data hiding methods is commonly analyzed by assuming a flat probability density function for the host signal, i.e. uniform inside each quantization cell and with its variance large enough to assuming that all the centroids occur with equal probability. This paper comes to fill a gap in watermarking theory, analyzing the exact performance of the Scalar Costa Scheme (SCS) facing additive Gaussian attacks when the former approximation is not valid, thus taking into account the host statistics. The accomplished analysis reveals that the true performance of such a scheme for an optimal selection of its parameters and low watermark to noise ratios (WNR) is never worse than that of classical spread-spectrum-based methods, in terms of achievable rate and probability of error, as it was thought so far. The reduction of SCS to a two-centroid problem allows the derivation of theoretical expressions which characterize its behavior for small WNR's, showing interesting connections with spread-spectrum (SS) and the Improved Spread Spectrum (ISS) method. Furthermore, we show that, in contrast to the results reported until now, the use of pseudorandom dithering in SCS-based schemes can have a negative impact in performance. Performance losses are also reported for the case in which a modulo reduction is undertaken prior to decoding. The usefulness of these results is shown in the computation of the exact performance in projected domains.

Özetçe Stereo 3B videoda, insanlarÕn bakÕúlardan biri yüksek kalitede olmak úartÕyla 3B videoyu yüksek kalitede algÕlayabildikleri iyi bilinmektedir. Bu nedenle, stereo video kodlamada, en iyi toplam oran -algÕlanan bozulma performansÕ ikinci bakÕúÕn uzamsal çözünürlü÷ü, çerçeve hÕzÕ ve/veya nicemleme parametresi birinci bakÕúa göre düúük tutularak elde edilebilir. Nesnel stereo video kalite metri÷i eúit olmayan hÕz tahsisinin baúarÕmÕ için çok önemli bir noktadÕr. AlgÕlanan 3B video kalitesi iki bakÕúÕn ortalama PSNR'Õ ile iyi örtüúmedi÷inden, iki PSNR de÷erinin a÷ÕrlÕklÕ bir kombinasyonu ile bir silkeleme ölçüsünü kullanan yeni bir nicel ölçme sistemini [1]'de önerdik. Biz bu bildiride PSNR a÷ÕrlÕklarÕnÕn farklÕ ölçekleme seçenekleri ve videolardaki uzamsal aktivite ile ba÷lantÕlÕ olmasÕ gereklili÷ini araútÕrmaktayÕz. Uzamsal aktivite bloklanma ve bulanÕklÕk bakÕmÕndan incelenmektedir. Belirli bazÕ deneyler için en iyi a÷ÕrlÕklar öznel kalite testi sonuçlarÕ ile nesnel ölçü skorlarÕ eúleútirilerek, yani aralarÕndaki en iyi korelasyon araútÕrÕlarak belirlenmektedir.

In this paper, the use of the fast Fourier transform (FFT) test to measure the integral nonlinearity (INL) of analog-todigital (A/D) converters is examined. The derived INL is a linear combination of Chebyshev polynomials, where the coefficients are the spurious harmonics of the output spectrum. The accuracy of the test is examined theoretically, in simulations and in practical devices, particularly for the critical (and typical) case when sudden jumps are present in the actual INL. The examined methodology appears to be very convenient when the device under test has high resolution (16-20 bits) and a smoothed approximation of the INL is sufficient, as the FFT test is in this case thousands of times faster than the customary histogram test and static nonlinearity test. Index Terms-Analog-to-digital (A/D) conversion, Chebyshev functions, discrete Fourier transform.

In this paper, the use of the fast Fourier transform (FFT) test to measure the integral nonlinearity (INL) of analog-todigital (A/D) converters is examined. The derived INL is a linear combination of Chebyshev polynomials, where the coefficients are the spurious harmonics of the output spectrum. The accuracy of the test is examined theoretically, in simulations and in practical devices, particularly for the critical (and typical) case when sudden jumps are present in the actual INL. The examined methodology appears to be very convenient when the device under test has high resolution (16-20 bits) and a smoothed approximation of the INL is sufficient, as the FFT test is in this case thousands of times faster than the customary histogram test and static nonlinearity test. Index Terms-Analog-to-digital (A/D) conversion, Chebyshev functions, discrete Fourier transform.

We compare two SNR scalable video codecs. The first codec (CODEC1) is a three-layer single-pass quantization algorithm based on H.263 and extends the work presented by Robers (see Master's Thesis Northwestern University, 1997) and Robers, Kondi and Katsaggelos (see Proc. SPIE Conf. on Visual Comm. and Image Proc., p.201-12, 1998). The second codec (CODEC2) implements three layer SNR scalability as described in Annex O of the H.263 standard by requantizing the DCT coefficients of the encoding error using finer quantizers than those used in the previous layer. By testing the two algorithms at various base and enhancement layer rates on both high and low motion sequences, the advantages and disadvantages of each codec are discussed and suitable applications are suggested for each one

We address the problem of distributed source coding, i.e. compression of correlated sources that are not co-located and/or cannot communicate with each other to minimize their joint description cost. In this work we tackle the related problem of compressing a source that is correlated with another source which is available only at the decoder. In contrast to prior information-theoretic approaches, we introduce a new construction and practical framework for tackling the problem based on the judicious incorporation of channel coding principles into this source coding problem. We dub our approach as distributed source coding using syndromes (DISCUS). We focus in this paper on trellis-structured constructions of the framework to illustrate its utility. Simulation results confirm the power of DISCUS, opening up a new and exciting constructive playing-ground for the distributed source coding problem. For the distributed coding of correlated i.i.d. Gaussian sources that are noisy versions of each other with “correlation-SNR” in the range of 12 to 20 dB, the DISCUS method attains gains of 7-15 dB in SNR over the Shannon-bound using “naive” independent coding of the sources