Randomness and Elements of Decision Theory Applied to Signals

Introduction in Matlab.- Random variables.- Probability distributions.- Joint random variables.- Random processes.- Binary pseudo-noise sequence generator.- Markov processes.- Noise in telecommunication systems.- Decision systems in noisy transmission channels.- Audio signals denoising using Independent Component Analysis.- Texture classification based on statistical models.- Histogram equalization.- PCM and DPCM.- NN and kNN supervised classification algorithms.- Supervised deep learning classification algorithms.- Texture feature extraction and classification using the Local Binary Patterns operator.

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• Probabilidade e Estatística
• Processamento de sinais
• Matemática para cientistas da computação
• Pesquisa operacional
• Decisões de gestão
• Engenharia electrónica

Random variables;Random prcoesses;Random Signals;Probability distributions;Joint random variables;pseudo-noise sequence generator;Markov processes;Decision systems;denoising;Histogram equalization;Pulse code modulation;kNN supervised classification;Convolutional Neural Network