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Seismic data must be interpreted using digital signal processing techniques in order to create accurate representations of petroleum;
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includes essential research and teaching material for digital signal and image processing individuals interested in learning seismic data;
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This short book is for students, professors and professionals interested in signal processing of seismic data using MATLAB (TM). The step;
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replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise;
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then focus on digital signal theory and relevant aspects of wave propagation and seismic modelling, followed by deconvolution and seismic;
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of applications in image and seismic data processing that demonstrate their use in real-world signal processing. For graduate students in electrical and;
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This volume is intended to provide the geophysical signal analyst with sufficient material to understand the usefulness of data covariance;
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Intended for a one-semester advanced graduate course in digital signal processing or as a reference for practicing engineers and;
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This book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to;
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This book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to;
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information science, this text will also be useful for advanced digital signal processing and real time digital signal processing courses for;
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communications, bio-inspired signal processing, seismic data processing, arithmetic transforms for spectrum computation, particle filtering;
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communications, bio-inspired signal processing, seismic data processing, arithmetic transforms for spectrum computation, particle filtering;
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of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both;
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from biomedical signals; higher order analysis in biomedical signals; advanced methods of signal and data processing in genomics and proteomics;
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advanced microsensors technologies require new and equally advanced methods of frequency signal processing in order to function at inreasingly high;
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, Optical Communication, Wireless Sensor Networks, MIMO Systems, MIMO Communications, Signal Processing for Communications e-Learning. Digital;
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presenting key concepts and providing the mathematical foundations and advanced algorithms that are essential to the design of any signal processing;
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As demand for applications working in extended frequency ranges increases, classical Digital signal processing (DSP) techniques, not;
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of digital signal processing, telecommunications and statistical data analysis. It will also be a valuable text to professional engineers;
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processing techniques for high-speed optical communication. In this book, numerous advanced digital signal processing techniques aiming at the;
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performance of digital circuitry and processors has prompted a switch to digital signal processing techniques rather than the traditional analog ones;
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Advances in digital signal processing algorithms and computer technology have combined to produce real-time systems with capabilities far;
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This publication deals with the application of advanced digital signal processing techniques and neural networks to various;
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signals - both basic and advanced. The author covers various advanced digital audio watermarking algorithms that can be used for copyright;
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, Nyquist and oversampled data conversion techniques, and multirate digital signal processing.. KEY TOPICS
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