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Document Type : Latin Dissertation
Language of Document : English
Record Number : 150257
Doc. No : ET22049
Main Entry : Yunbin Deng
Title Proper : Mixed-Signal VLSI Robust Time-Frequency Feature Extraction
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Robust feature extraction is critical to pattern recognition and intelligent systems. Theproblem of extracting reliable features from real-world signals is challenging because thesesignals are embedded in non-stationary noise; real-time operation requires fast adaptation;and mobile operation requires miniature hardware with low-power consumption. The needfor robust real-time, and low-power feature extraction solutions calls for an integrative ap-proach that combines adaptive signal processing, machine learning, and micropower VLSIdesign.This dissertation presents time-frequency feature extraction algorithms, inspired by bi-ological models of auditory processing, for robust feature extraction. The algorithms mapefficiently onto massive parallel VLSI hardware to provide real-time operation. Analogmodels of computation are combined with digital...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL45245.pdf
Title and statement of responsibility and : Mixed-Signal VLSI Robust Time-Frequency Feature Extraction [Thesis]
 
 
 
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