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Advanced Digital Signal Processing and Noise Reduction

component analysis* Comprehensive coverage of advanced digital signal processing and noise reduction methods for communication and information;

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Advanced Signal Analysis and its Applications to Mathematical Physics

The mathematical tools used in signal analysis involve differential and difference equations, integral equations, matrix algebra and;

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Advanced Methods of Biomedical Signal Processing

from biomedical signals; higher order analysis in biomedical signals; advanced methods of signal and data processing in genomics and proteomics;

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Handbook of Fourier Analysis & Its Applications

Fourier analysis has many scientific applications - in physics, number theory, combinatorics, signal processing, probability theory;

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Applications of Advanced Signal Analysis

The mathematical tools used in signal analysis involve differential and difference equations, integral equations, matrix algebra and;

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EEG/ERP Analysis

consists of 13 chapters and includes the advanced techniques used for signal enhancement, source localization, data fusion, classification, and;

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EEG/ERP Analysis

consists of 13 chapters and includes the advanced techniques used for signal enhancement, source localization, data fusion, classification, and;

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First Course In Wavelets With Fourier Analysis

of Fourier analysis and wavelets, while uniquely presenting signal analysis applications and problems. Essential and fundamental ideas are presented;

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Signal Processing

, video signal processing, pattern analysis, pattern recognition, artificial intelligence, decision making, control systems, and many more. In the;

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Practical Biomedical Signal Analysis Using MATLAB (R)

processing methods and applications, this second edition of Practical Biomedical Signal Analysis Using MATLAB (R) also offers practical guidance on;

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Mathematical Foundations for Signal Processing, Communications, and Networking

design, analysis, and optimization of signal processing algorithms, modern communication systems, and networks. Helping readers master key;

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Biomedical Signal Analysis

The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a;

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Signal Processing and Machine Learning with Applications

their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and;

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New Digital Signal Processing Methods

methods in signal analysis and treatment are introduced and described in depth. More in details, the book covers the following new advanced topics;

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Nonlinear Biomedical Signal Processing, Volume 1

>Uncertainty management Analysis of biomedical signals A guided tour of neural networks Application of algorithms to EEG and;

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Partial-Update Adaptive Signal Processing

/>Features:? Advanced analysis and design tools? Application examples illustrating the use of partial-update adaptive signal;

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Advanced Signal Processing and Digital Noise Reduction

of applications in speech technology, audio signal processing, channel equalisation, radar signal processing, pattern analysis, data forecasting, decision;

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Brief Notes in Advanced DSP

Based on the authors' research in Fourier analysis, Brief Notes in Advanced DSP: Fourier Analysis with MATLAB (R) addresses many concepts;

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Wavelets and Signal Processing

reference work for advanced students and practitioners in wavelets, and wavelet transforms, signal processing and time-frequency signal analysis;

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Signal Processing for Neuroscientists

section developed by the author. Since the modeling of systems and signal analysis are closely related, integrated presentation of these topics;

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Learning Approaches in Signal Processing

Coupled with machine learning, the use of signal processing techniques for big data analysis, Internet of things, smart cities, security;

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Applied Wavelet Analysis with S-PLUS

, in addition to wavelets, a whole range of related signal processing techniques such as wavelet packets, local cosine analysis, and matching pursuits;

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Advanced Techniques for Audio Watermarking

signals - both basic and advanced. The author covers various advanced digital audio watermarking algorithms that can be used for copyright;

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Functional Analysis and Applications

This self-contained textbook discusses all major topics in functional analysis. Combining classical materials with new methods, it supplies;

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Window Functions and Their Applications in Signal Processing

on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively;

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Window Functions and Their Applications in Signal Processing

on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively;

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Compressed Sensing in Li-Fi and Wi-Fi Networks

covering advanced signal processing, efficient data processing algorithms, and telecommunications. After a thorough review of the basic theory;

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