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基于粒子群PSO+随机梯度下降SGD优化器的Pytorch训练框架

Code to validate the "Particle swarm optimization of deep neural networks architectures for image classification" paper.

Learn about particle swarm optimization (PSO) through Python!

Multi-Objective PSO (MOPSO) in MATLAB

This script implements the hybrid of PSO and GWO optimization algorithm.

使用粒子群算法优化的RBF神经网络进行预测。RBF neural network optimized by particle swarm optimization is used for prediction.

This is an unofficial PyTorch 1.0.1 implementation of the papr Neural Aggregation Network for Video Face Recognition. CVPR 2017

Source code for paper: Semantic Communications with Discrete-time Analog Transmission: A PAPR Perspective

Allows to reproduce all figures from "Pruned DFT Spread FBMC: Low PAPR, Low Latency, High Spectral Efficiency", IEEE Transactions on Communications, 2018

An OFDM modulation commutation system on Android phones using sound wave

basic and some improved ACO

ACO algorithm for TSP problem

code for underwater acoustics modeling

Optimization algorithms written in Python and MATLAB

Various functions for acoustics and audio signal processing.

Acoustic signal processing and underwater acoustic communications.

In oceanic remote sensing operations, underwater acoustic target recognition is always a difficult and extremely important task of sonar systems, especially in the condition of complex sound wave p…

use some algorithm to solve the Route Planning. Including Genetic Algorithm(GA),Particle Swarm Optimization(PSO),ant colony optimization(ACO).

Deep-Waveform: A Learned OFDM Receiver Based on Deep Complex-valued Convolutional Networks

The problem of epilepsy has grown exponentially and is now considered as one of the most prevailing neurological disorders affecting around 50 million people around the globe. Epilepsy is identifie…

a 1d attention CNN for signal classification written in tensorflow

Classification of EEG signals into three categories: normal, interictal, and ictal, using 2D convolution neural network =

This example shows how to build and train a convolutional neural network (CNN) from scratch to perform a classification task with an EEG dataset.

The project is about applying CNNs to EEG data from CHB-MIT to predict seizure

This repository contains the trained deep learning models for the detection and prediction of Epileptic seizures.

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.