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Quantum-Mechanical Signal Processing and Spectral Analysis

Quantum-Mechanical Signal Processing and Spectral Analysis describes the novel application of quantum mechanical methods to signal;

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Signal Processing with Free Software

files and elementary operations on signals and then presents the first tools to signal analysis such as temporal and frequency characteristics;

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A Course in Digital Signal Processing

spectral analysis, sinusoidal signal analysis, and the effect of noise. It also covers FIR and IIR filters, including detailed design procedures;

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Random Signal Analysis

transformation, spectral analysis of stationary and narrow band random process are discussed in detail. With abundant exercises, this book is an;

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Digital Spectral Analysis

for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation;

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Digital Spectral Analysis MATLAB (R) Software User Guide

techniques and algorithms, plus time versus frequency analysis. The spectral demonstrations use MATLAB software that encompasses the full experience;

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Phonocardiography Signal Processing

The auscultation method is an important diagnostic indicator for hemodynamic anomalies. Heart sound classification and analysis play an;

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Two-dimensional Signal Analysis

This title sets out to show that 2-D signal analysis has its own role to play alongside signal processing and image processing;

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Signal Processing in Magnetic Resonance Spectroscopy with Biomedical Applications

) as the unique polynomial quotient for the spectral analysis of MR time signals. They prove that residual spectra are necessary but not;

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Signal Processing in Magnetic Resonance Spectroscopy with Biomedical Applications

) as the unique polynomial quotient for the spectral analysis of MR time signals. They prove that residual spectra are necessary but not;

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Optimal and Adaptive Signal Processing

algorithm, applications of adaptive filtering, algorithms and structures for adaptive filtering, spectral analysis, and array signal processing;

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Optimal and Adaptive Signal Processing

algorithm, applications of adaptive filtering, algorithms and structures for adaptive filtering, spectral analysis, and array signal processing;

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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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Hyperspectral Data Processing

extraction, unsupervised linear spectral mixture analysis, hyperspectral information compression, hyperspectral signal coding and characterization;

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Advanced Digital Signal Processing and Noise Reduction

of statistical signal processing and noise reduction methods. * Two new chapters on MIMO systems, correlation and Eigen analysis and independent;

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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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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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Resolving Spectral Mixtures

decades. Spectral unmixing is a topic of interest in statistics, chemometrics, signal processing, and image analysis. For decades;

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Random Signal Processing

This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral;

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Random Signal Processing

This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral;

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Fourier Theory in Optics and Optical Information Processing

comprehensive understanding of Fourier transform and spectral analysis in optics, image processing, and signal processing. Written by a world renowned;

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Advanced Signal Processing

processing Ideal for upper-undergraduate and graduate courses, this engineering textbook offers key signal analysis principles and uses and;

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Wigner Transform, The

general mathematical framework, and then through applications to quantum mechanics. The Wigner transform was introduced by Eugene Wigner in 1932;

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Wigner Transform, The

general mathematical framework, and then through applications to quantum mechanics. The Wigner transform was introduced by Eugene Wigner in 1932;

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Signal Processing

on the computational aspects. This book covers linear system analysis, probability theory, random signals, spectral analysis, estimation;

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An Introduction to Digital Signal Processing

, Systems and Simulations, and Spectral Analysis. The book is focused on basic concepts of digital signal processing, MATLAB simulation and;

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