Fundamentals Of Stochastic Signals, Systems And Estimation Theory 2Ed (Hb)

This book is intended for undergraduate students, graduate students and practical engineers, specializing in the areas ofelectrical communications, signalprocessing and automatic control. It has emergedfrom various lecture notes, in Serbian and in English, that we have compiledand used in different courses at Faculty ofElectrical Engineering, University ofBelgrade, since 1980. The specializing in the areas of electrical communications, signal processing and automatic control required background is a course in a probability theory and basic linear dynamic systems and signals theory (transferfunctions and state space). Appendix A provides a short review ofLaplace and Z-transformfor those who need it. Moreover, one advantageofmodern control theory is that it employs matrix algebra, which results in a simplification in notation and mathematical manipulations when dealing with multivariable systems. Therefore, a brief review of the matrix algebra is presented in Appendix B. Generally speaking, the goal ofthis textbook is to clarify the terms digital filtering, Kalman filtering and other types ofestimation techniques appearing quite often in the present-day professional literature. In the electrical engineering curriculum, a course in Stochastic signals, systems and estimation is introduced to accompany underlying courses in Control systems, Communication systems and Signal processing. In addition, many problems in wireless communications, networking, electronics, photonics, power systems and robotics are now studiedfrom the stochastic signals and systems point of view. This textbook can be also used by other engineering students interested in these topics, especially biomedical, aerospace, civil, traffic, mechanicaland industrial engineering students.

From the reviews of the second edition:

"In the present textbook basic concepts of linear stochastic systems, stochastic signals, modeling and analysis, as well as model-based signal processing are described using the transfer function model and the state space model. ... Many worked examples are given within the text. The book is suitable for undergraduate and graduate courses in the field of linear stochastic systems, signal processing and automatic control." (Kurt Marti, Zentralblatt MATH, Vol. 1156, 2009)

“The book presents the fundamentals of stochastic processes and systems, with emphasis on estimation theory. It is appropriate for both undergraduate and graduate students and for engineers in the fields of communications, signal processing, and automatic control. It contains several examples and experiments performed by using Matlab. ... Appendices on Laplace and Z-transforms, matrix analysis, and probability density functions and references end the book.”­­­ (Antonio Napolitano, Mathematical Reviews, Issue 2010 j)