Digital Processing of Random Signals: Theory and Methods
Digital Processing of Random Signals: Theory and Methods
This excellent advanced text rigorously covers several topics related to random signal processing. Geared toward students of electrical engineering, its material is sufficiently general to be applicable to other engineering fields. It features numerous homework problems of varying difficulty, with ample hints for the more challenging problems, and solutions for those with results that reappear in later chapters.
Author Boaz Porat, Professor of Electrical Engineering at the Israel Institute of Technology (Technion), in Haifa, introduces stationary processes and discusses their structure and main properties. He proceeds to examinations of statistical estimation theory, classical spectrum estimation, and parameter estimation theory for Gaussian processes. Subsequent chapters explore autoregressive parameter estimation and its role in adaptive estimation techniques, in addition to estimation methods based on high-order statistical analysis and the time-frequency analysis of nonstationary signals. Four helpful appendixes conclude the text.
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This excellent advanced text rigorously covers several topics related to random signal processing. Geared toward students of electrical engineering, its material is sufficiently general to be applicable to other engineering fields. It features numerous homework problems of varying difficulty, with ample hints for the more challenging problems, and solutions for those with results that reappear in later chapters.
Author Boaz Porat, Professor of Electrical Engineering at the Israel Institute of Technology (Technion), in Haifa, introduces stationary processes and discusses their structure and main properties. He proceeds to examinations of statistical estimation theory, classical spectrum estimation, and parameter estimation theory for Gaussian processes. Subsequent chapters explore autoregressive parameter estimation and its role in adaptive estimation techniques, in addition to estimation methods based on high-order statistical analysis and the time-frequency analysis of nonstationary signals. Four helpful appendixes conclude the text.
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