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Statistical Signal Processing for Neuroscience and Neurotechnology

This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving;

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Neurotechnology

This book focuses on recent advances and future trends in the methods and applications of technologies that are used in neuroscience for;

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Fundamentals Of Statistical Signal Processing

, etc. A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing;

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Signal Processing in Auditory Neuroscience

Signal Processing in Auditory Neuroscience: Temporal and Spatial Features of Sound and Speech discusses how the physical attributes;

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Multirate Statistical Signal Processing

Multirate Statistical Signal Processing introduces a statistical theory for extracting information from related signals with different;

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Statistical Signal Processing in Engineering

A problem-solving approach to statistical signal processing for practicing engineers, technicians, and graduate students This book takes a;

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Statistical Methods in Control & Signal Processing

Presenting statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas, this;

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Signal Processing in Neuroscience

methods in the context of NSP. Neuronal Signal Processing is a comparatively new field in computer sciences and neuroscience, and;

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Multiscale Signal Analysis and Modeling

, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and;

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Stevens' Handbook of Experimental Psychology

and cognitive neuroscience; the stop-signal paradigm; hypothesis testing and statistical inference; model comparison in psychology; fmri;

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Digital and Statistical Signal Processing

digital signal processing and statistical signal processing. The solutions are based directly on the math-formulas given in extensive tables;

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Digital and Statistical Signal Processing

digital signal processing and statistical signal processing. The solutions are based directly on the math-formulas given in extensive tables;

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Multimedia Signal Processing

range of important topics are covered in basic signal processing, model-based statistical signal processing and their applications. Part 1;

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An Introduction to Statistical Signal Processing

This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to;

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An Introduction to Statistical Signal Processing

This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to;

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Handbook of Formulas and Tables for Signal Processing

integral tables, formulas of algebra, formulas of trigonometry - the text includes: Material for the deterministic and statistical signal;

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Signal Processing and Data Analysis

This book presents digital signal processing theories and methods and their applications in data analysis, error analysis and statistical;

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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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Intelligent Signal Processing

is extracted from incoming signal and noise data, making few assumptions about the statistical structure of signals and their environment. Intelligent;

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Bioelectrical Signal Processing in Cardiac and Neurological Applications

potentials, EMG) Covers both classical and recent signal processing techniques Emphasis on model-based statistical signal;

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EEG Signal Processing and Feature Extraction

This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal;

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EEG Signal Processing and Feature Extraction

This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal;

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Digital Signal Processing with Kernel Methods

of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both;

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Cooperative and Graph Signal Processing

, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the;

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Statistical Signal Processing

statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical;

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Statistical Signal Processing

statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical;

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Signal Processing in Medicine and Biology

statistical modeling of electroencephalograph data for predicting or detecting seizure, stroke, or Parkinson's; machine learning methods and their;

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