统计与随机过程在信号处理中的应用（改编版）
￥57.00定价
作者： Henry Stark，John W.Woods原著，孟桥改编
出版时间：2008年1月
出版社：高等教育出版社
- 高等教育出版社
- 9787040225822
- 1版
- 131276
- 0045153854-0
- 异16开
- 2008年1月
- 719
- 工学
- 信息与通信工程
- TN911.6
- 电子信息类
- 研究生、本科
内容简介
The first editiofl of this book (1986) grew out of a set of notes used by the authorsto teach two one-semester courses on probability and random processes at Rensse-laer Polytechnic Institute (RPI). At that time the probability course at RPI was re-quired of all students in the Computer and Systems Engineering Program and was a highly recommended elective for students in closely related areas. While many un-dergraduate students took the course in the junior year, many seniors and first-year graduate students took the course for credit as well. Then, as now, most of the stu-dents were engineering students. To serve these students well, we felt that we should be rigorous in introducing fundamental principles while furnishing many op- portunities for students to develop their skills at solving problems.
目录
Introduction to Probability 1.1 INTRODUCTION:WHY STUDY PROBABILITY? 1.2 THE DIFFERENT KINDS OF PROBABILITY A. Probability as Intuition B. Probability as the Ratio of Favorable to Total Outcomes (Classical Theory) C. Probability as a Measure of Frequency of Occurrence D. Probability Based on an Axiomatic Theory 1.3 MISUSES,MISCALCULATIONS,AND PARADOXES 1N PROBABILITY 1.4 SETS,FIELDS,AND EVENTS Examples of Sample Spaces 1.5 AXIOMATIC DEFINITION OF PROBABILITY 1.6 JOINT, CONDITIONAL,AND TOTAL PROBABILITIES;INDEPENDENCE 1.7 BAYES' THEOREM AND APPLICATIONS 1.8 COMBINATORICS Occupancy Problems Extensions and Applications 1.9 BERNOULLI TRIALS--BINOMIAL AND MULTINOMIAL PROBABILITY LAWS Multinomial Probability Law 1.10 ASYMPTOTIC BEHAVIOR oF THE BINOMIAL LAW： THE POISSON LAW 1.11 NORMAL APPROXIMATION TO THE BINOMIAL LAW 1.12 SUMMARY PROBLEMS REFERENCES2 Random Variables 2.1 INTRODUCTION 2.2 DEFINITION OF A RANDOM VARIABLE 2.3 PROBABILITY DISTRIBUTION FUNCTION 2.4 PROBABILITY DENSITY FUNCTION(pdf) Four Other Common Density Functions More Advanced Density Functions 2.5 CONTINUOUS,DISCRETE,AND MIXED RANDOM VARIABLES Examples of Probability Mass Functions 2.6 CONDITIONAL AND JOINT DISTRIBUTIONS AND DENSITIES 2.7 FAILURE RATES 2.8 FUNCTIONS OF A RANDOM VARIABLE 2.9 SOLVING PROBLEMS OF THE TYPE 2.10 SOLVING PROBLEMS OF THE TYPE 2.11 SOLVING PROBLEMS OF THE TYPE W=h(X,Y) 2.12 SUMMARY PROBLEMS REFERENCES ADDITIONAL READING3. Expectation and Introduction to Estimation 3.1 EXPECTED VALUE OF A RANDOM VARIABLE On the Validity of Equation 3.1 -8 3.2 CONDITIONAL EXPECTATIONS Conditional Expectation as a Random Variable……
