000			03745cam a22002894a 4500
008			081218s2006 nyua b 001 0 eng
010			_a2005051721
020			_a9780387241579 (acid-free paper)
035			_a(Sirsi) u1026
040			_aEG-CaNU _cEG-CaNU _dEG-CaNU
050	0	0	_aQA273 _b .K326 2006
082	0	0	_a519.20113 _2 22
100	1		_aKay, Steven M., _d 1951- _9121
245	1	0	_aIntuitive probability and random processes using MATLAB / _c Steven M. Kay.
260			_aNew York : _b Springer, _c c2006.
300			_axviii, 833 p. : _b ill. ; _c 27 cm.
504			_aIncludes bibliographical references and index.
505	0		_aIntroductionp. 1 Computer simulationp. 13 Basic probabilityp. 37 Conditional probabilityp. 73 Discrete random variablesp. 105 Expected values for discrete random variablesp. 133 Multiple discrete random variablesp. 167 Conditional probability mass functionsp. 215 Discrete N-dimensional random variablesp. 247 Continuous random variablesp. 285 Expected values for continuous random variablesp. 343 Multiple continuous random variablesp. 377 Conditional probability density functionsp. 433 Continuous N-dimensional random variablesp. 457 Probability and moment approximations using limit theoremsp. 485 Basic random processesp. 515 Wide sense stationary random processesp. 547 Linear systems and wide sense stationary random processesp. 597 Multiple wide sense stationary random processesp. 641 Gaussian random processesp. 673 Poisson random processesp. 711 Markov chainsp. 739 Table of Contents provided by Blackwell. All Rights Reserved.
520			_aIntuitive Probability and Random Processes using MATLAB(R) is an introduction to probability and random processes that merges theory with practice. Based on the author's belief that only "hands-on" experience with the material can promote intuitive understanding, the approach is to motivate the need for theory using MATLAB examples, followed by theory and analysis, and finally descriptions of "real-world" examples to acquaint the reader with a wide variety of applications. The latter is intended to answer the usual question "Why do we have to study this?" Other salient features are: *heavy reliance on computer simulation for illustration and student exercises *the incorporation of MATLAB programs and code segments *discussion of discrete random variables followed by continuous random variables to minimize confusion *summary sections at the beginning of each chapter *in-line equation explanations *warnings on common errors and pitfalls *over 750 problems designed to help the reader assimilate and extend the concepts Intuitive Probability and Random Processes using MATLAB(R) is intended for undergraduate and first-year graduate students in engineering. The practicing engineer as well as others having the appropriate mathematical background will also benefit from this book. About the Author Steven M. Kay is a Professor of Electrical Engineering at the University of Rhode Island and a leading expert in signal processing. He has received the Education Award "for outstanding contributions in education and in writing scholarly books and texts..." from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.
630	0	0	_aCIT. _914
630	0	0	_aMATLAB _v Textbooks. _9122
650		0	_aProbabilities _x Computer simulation _v Textbooks. _9123
650		0	_aStochastic processes _x Computer simulation _v Textbooks. _9124
596			_a1
999			_c37 _d37