000			02712cam a22003134a 4500
008			090302s2006 nyua b 001 0 eng
010			_a2006298231
020			_a9780521864701
020			_a0521864704
035			_a(Sirsi) u1148
040			_aEG-CaNU _cEG-CaNU _dEG-CaNU
042			_ancode
082	0	0	_a519.2 _2 22
100	1		_aGubner, John A. _9602
245	1	0	_aProbability and random processes for electrical and computer engineers / _c John A. Gubner.
260			_aNew York ; _a Cambridge : _b Cambridge University Press. _c 2006.
300			_axii, 628 p. : _b ill. ; _c 26 cm.
500			_aText on lining papers.
504			_aIncludes bibliography and index.
505	0		_aPreface -- 1. Introduction to probability -- 2. Introduction to discrete random variables -- 3. More about discrete random variables -- 4. Continuous random variables -- 5. Cumulative distribution functions and their applications -- 6. Statistics -- 7. Bivariate random variables -- 8. Introduction to random vectors -- 9. Gaussian random vectors -- 10. Introduction to random processes -- 11. Advanced concepts in random processes -- 12. Introduction to Markov chains -- 13. Mean convergence and applications -- 14. Other modes of convergence -- 15. Self similarity and long-range dependence -- Bibliography -- Index.
520			_aThe theory of probability is a powerful tool that helps electrical and computer engineers to explain, model, analyze, and design the technology they develop. The text begins at the advanced undergraduate level, assuming only a modest knowledge of probability, and progresses through more complex topics mastered at graduate level. The first five chapters cover the basics of probability and both discrete and continuous random variables. The later chapters have a more specialized coverage, including random vectors, Gaussian random vectors, random processes, Markov Chains, and convergence. Describing tools and results that are used extensively in the field, this is more than a textbook; it is also a reference for researchers working in communications, signal processing, and computer network traffic analysis. With over 300 worked examples, some 800 homework problems, and sections for exam preparation, this is an essential companion for advanced undergraduate and graduate students. Further resources for this title, including solutions (for Instructors only), are available online at www.cambridge.org/9780521864701.
630	0	0	_aCIT. _914
650		0	_aProbabilities. _9603
650		0	_aStochastic processes. _9604
650		0	_aElectric engineering _x Mathematics. _9330
650		0	_aComputer engineering _x Mathematics. _9605
692			_aCIT-GT
596			_a1
999			_c171 _d171