Spectrum Estimation and System Identification (Lecture Notes in Mathematics; 1542)
| Author | : | |
| Rating | : | 4.87 (820 Votes) |
| Asin | : | 0387940235 |
| Format Type | : | paperback |
| Number of Pages | : | 327 Pages |
| Publish Date | : | 2017-08-14 |
| Language | : | English |
DESCRIPTION:
About the AuthorUnnikrishna Pillai, is a Professor of Electrical and Computer Engineering at Polytechnic School of Engineering, New York University(NYU). Pillai teaches Probability, Stochastic Processes, Detection, Estimation all catered to Electrical Engineering applications. He has coauthored five textbooks/monographs and two e-books mostly related to electrical engineering. Within the classroom, he has started generating short video sessions (on You Tube) to complement (compensate) his lectures, wherein students can review key material and examples and work out problems before and after the class sessions.. Pill
He has coauthored five textbooks/monographs and two e-books mostly related to electrical engineering. His research interests include system identification, adaptive signal processing, synthetic aperture radar (SAR) imaging, radar signal processing and waveform design as well as Portfolio design. Pillai joined the Electrical Engineering department of Polytechnic Institute of New York (Brooklyn Poly) in 1985 as an Assistant Professor after graduating from University of Pennsylv
Such an approximation has important applications in distributed system theory, simulation of systems governed by partial differential equations, and analysis of differential equations with delays. Spectrum estimation refers to analyzing the distribution of power or en ergy with frequency of the given signal, and system identification refers to ways of characterizing the mechanism or system behind the observed sig nal/data. Positive functions have been used to study interpolation problems in the past, and although the spectrum extension problem falls within this scope, surprisingly the system identification problem can also be analyzed in this context in an interesting manner. This book is intended as an introductory graduate level textbook and as a reference book for engineers and researchers.. One useful result in this connection is regarding rational and stable approximation of nonrational transfer functions both in the single-channel case and the multichannel case. A new outlook to spectrum estimation and system identification is pre sented here by making use of the powerful concepts of positive functions and bounded functions. Such an identification allows one to predict the system outputs, and as a result this has considerable impact in several areas such as speech processing, pattern recognition, target identification, seismology, and signal processing. An indispensable tool in classical network analysis and synthesis problems, positive functions and
"Too tough for non-expert" according to A Customer. It is for expert in this field, not even for graduate students