Intended AudienceTrade
SynopsisThe aim of this book on statistical signal processing is to develop, in the form of separate lectures, an understanding of the basic concepts of this topic starting with introductory digital signal processing (DSP) material. The intended audience is the group of M.Sc. candidates of the Electrical Engineering Department, College of Engineering, University of Baghdad, specializing in electronics and communication engineering, and control and computer engineering. An understanding of statistical signal processing in its theoretical and practical aspects is crucial to these two specializations. The book is divided into ten lectures, of which the first four are dedicated to basic DSP concepts. This was done to familiarize the intended M.Sc. students, usually having different backgrounds, with these important concepts in case a thorough treatment of DSP was missing from the undergraduate curricula of some of the students.The line of thought enchaining the different lectures in the book has been influenced by the teaching experience and research activity of the author. With the afore-mentioned specific specimen of students in mind, and in order to lay the foundations for relevant future studies and research for them, the author has focused on topics she considers fundamental and as having important applications. These topics include random signal modelling and spectrum estimation, optimum filtering and linear prediction, and adaptive filtering. The applications of signal modelling are diverse such as the synthesis of artificial signals similar to the natural ones in speech for instance, and parameter extraction for pattern recognition applications. Spectral estimation finds many applications in medical diagnosis, speech analysis, radar and sonar, amongst others. Optimum filtering, linear prediction and adaptive filtering find uses in many control and communications applications such as system identification and the theoretically related application of communication channel estimation, acoustic echo cancellation, system inversion and channel equalization, signal prediction for communication purposes and noise reduction, and interference cancellation. To keep the set of lectures concise and suitable for a one-semester course, only aspects involving temporal filtering have been considered. Spatial filtering encountered in array signal processing will not be dealt with owing to the introductory nature of the book.