Random Signals And Noise
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📒Introduction To Random Signals And Noise ✍ Wim C. Van Etten
✏Introduction to Random Signals and Noise Book Summary : Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding, this text provides a clear introduction to the fundamentals of stochastic processes and their practical applications to random signals and noise. With worked examples, problems, and detailed appendices, Introduction to Random Signals and Noise gives the reader the knowledge to design optimum systems for effectively coping with unwanted signals. Key features: Considers a wide range of signals and noise, including analogue, discrete-time and bandpass signals in both time and frequency domains. Analyses the basics of digital signal detection using matched filtering, signal space representation and correlation receiver. Examines optimal filtering methods and their consequences. Presents a detailed discussion of the topic of Poisson processes and shot noise. An excellent resource for professional engineers developing communication systems, semiconductor devices, and audio and video equipment, this book is also ideal for senior undergraduate and graduate students in Electronic and Electrical Engineering.
📒Random Signals And Noise ✍ Shlomo Engelberg
✏Random Signals and Noise Book Summary : Understanding the nature of random signals and noise is critically important for detecting signals and for reducing and minimizing the effects of noise in applications such as communications and control systems. Outlining a variety of techniques and explaining when and how to use them, Random Signals and Noise: A Mathematical Introduction focuses on applications and practical problem solving rather than probability theory. A Firm Foundation Before launching into the particulars of random signals and noise, the author outlines the elements of probability that are used throughout the book and includes an appendix on the relevant aspects of linear algebra. He offers a careful treatment of Lagrange multipliers and the Fourier transform, as well as the basics of stochastic processes, estimation, matched filtering, the Wiener-Khinchin theorem and its applications, the Schottky and Nyquist formulas, and physical sources of noise. Practical Tools for Modern Problems Along with these traditional topics, the book includes a chapter devoted to spread spectrum techniques. It also demonstrates the use of MATLAB® for solving complicated problems in a short amount of time while still building a sound knowledge of the underlying principles. A self-contained primer for solving real problems, Random Signals and Noise presents a complete set of tools and offers guidance on their effective application.
📒Probability Random Variables And Random Signal Principles ✍ Peyton Z. Peebles
✏Probability Random Variables and Random Signal Principles Book Summary : This concise introduction to probability theory for undergraduate electrical engineers offers a logical organization which stresses the fundamentals of the subject. The topics have been chosen to flow logically from simple to advanced. Examples and applications illustrating the theory are featured throughout the book, including discussions of noise figures and noise and random signals in systems, and over 800 exercises are included.
📒Random Signals And Noise ✍ Hemchandra Shertukde
✏Random Signals and Noise Book Summary :
📒Principles Of Random Signal Analysis And Low Noise Design ✍ Roy M. Howard
✏Principles of Random Signal Analysis and Low Noise Design Book Summary : Describes the leading techniques for analyzing noise. Discusses methods that are applicable to periodic signals,aperiodic signals, or random processes over finite or infiniteintervals. Provides readers with a useful reference when designing ormodeling communications systems.
📒Random Signal Processing ✍ Dwight F. Mix
✏Random Signal Processing Book Summary : Providing detailed coverage of Wiener filtering and Kalman filtering, this book presents a coherent treatment of estimation theory and an in-depth look at detection theory for communication and pattern recognition.
📒An Introduction To Random Signals And Communication Theory ✍ Bhagwandas Pannalal Lathi
✏An introduction to random signals and communication theory Book Summary :
📒Random Signal Analysis ✍ Jie Yang
✏Random Signal Analysis Book Summary : A fundamental introduction to the delopment of random signal processing with an emphasis on analysis. Linear transformation, nonlinear transformation, spectral analysis of stationary and narrow band random process are discussed in detail. With abundant exercises, this book is an essential reference for graduate students, scientists and practitioners in electronical engineering and signal processing.
📒Detection Of Signals In Noise ✍ Anthony D. Whalen
✏Detection of Signals in Noise Book Summary : Detection of Signals in Noise serves as an introduction to the principles and applications of the statistical theory of signal detection. The book discusses probability and random processes; narrowband signals, their complex representation, and their properties described with the aid of the Hilbert transform; and Gaussian-derived processes. The text also describes the application of hypothesis testing for the detection of signals and the fundamentals required for statistical detection of signals in noise. Problem exercises, references, and a supplementary bibliography are included after each chapter. Students taking a graduate course in signal detection theory.
📒Advanced Theory Of Signal Detection ✍ Iickho Song
✏Advanced Theory of Signal Detection Book Summary : This monograph contains a number of problems with signal detection theory, presenting a generalized observation model for signal detection problems. The model includes several interesting and common special cases, such as those describing additive noise, multiplicative noise and signal-dependent noise.