Vaidyanathan P.P. The Theory of Linear Prediction

Издательство Marcel Dekker, 1995, -329 pp. Virtually all physical systems are nonlinear. It is often possible to approximate them by linear models and so utilize the rich theory of linear systems in analyzing and predicting the behaviour of a physical system. When a good enough linear approximation does not exist, and one is forced to use nonlinear models, the analysis becomes much more demanding. It is well known that there are no general appro...

This text provides a complete introduction to signal analysis. Inclusion of fundamental ideas—analog and discrete signals, linear systems, Fourier transforms, and sampling theory—makes it suitable for introductory courses, self-study, and refreshers in the discipline. But along with these basics, Signal Analysis: Time, Frequency, Scale, and Structure gives a running tutorial on functional analysis—the mathematical concepts that generalize linear...

Many interesting topics are studied in digital signal and image processing, and. one of them is the theory and application of Fourier analysis. The Fourier. transformation is the most used tool when analyzing and solving problems. n the framework of linear systems that describe and approximate di?erent. physical systems in practice. In digital signal processing (DSP), this transfor-. mation gives the push for developing other fast discrete transf...

Издательство CRC Press, 2004, -535 pp. Книга из серии «The Electrical Engineering and Applied Signal Processing Series» Nonlinear signal processing methods continue to grow in popularity and use. This growth is due to one factor—performance. While it is true that linear methods continue to dominate in current practice, nonlinear methods are making steady progress in moving from theoretical explorations to practical implementations. Clearly, the...

Издательство John Wiley, 2001, -592 pp. Analyzing and designing systems with the help of suitable mathematical tools is extraordinarily important for engineers. Accordingly, systems theory is a part of the core curriculum of modern electrical engineering and serves the foundation of a large number of subdisciplines. Indeed, access to special engineering demands a mastery of systems theory. An introduction to systems theory logically begins with...

Издательство Now Publishers, Серия Foundations and Trends in Signal Processing, 2010, -152 pp. A survey of LPC and a History of Real-time Digital Speech on Packet Networks In December 1974 the first real-time conversation on the ARPAnet took place between Culler-Harrison Incorporated in Goleta, California, and MIT Lincoln Laboratory in Lexington, Massachusetts. This was the first successful application of real-time digital speech communication...

Издательство InTech, 2010, -400 pp. The seminal Kalman filter paper, entitled A new approach to linear filtering and prediction problems, and published in 1960, reformulated the Wiener problem and proposed a new solution based on state transition, avoiding the stationary limitations of the Wiener filter and giving a more suitable algorithm to be implemented in computers. This paper concludes with a prophetic sentence: . The Wiener problem is sh...

Издательство Artech House, 2005, -807 pp. The principal goal of this book is to provide a unified introduction to the theory, implementation, and applications of statistical and adaptive signal processing methods.We have focused on the key topics of spectral estimation, signal modeling, adaptive filtering, and array processing, whose selection was based on the grounds of theoretical value and practical importance. The book has been primarily wri...

2nd Edition. John Wiley and Sons, Ltd, 2000, - 473 pages. Introduction. Noise and Distortion. Probability Models. Bayesian Estimation. Hidden Markov Models. Wiener Filters Adaptive Filters. Linear Prediction Models. Power Spectrum and Correlation. Interpolation. Spectral Subtraction. Impulsive Noise. Transient Noise Pulses. Echo Cancellation. Channel Equalisation and Blind Deconvolution.

John Wiley and Sons, Ltd, 2006. Introduction. Noise and Distortion. Probability and Information Models. Bayesian Inference. Hidden Markov Models. Least Square Error Filters. Adaptive Filters. Linear Prediction Models. Power Spectrum and Correlation. Interpolation. Spectral Amplitude Estimation. Impulsive Noise. Transient Noise Pulses. Echo Cancellation. Channel Equalisation and Blind Deconvolution. Speech Enhancement in Noise. Noise in Wireless C...