E. Wong – författare

For most people, intuitive notions concerning probabilities are connected with relative frequencies of occurrence. For example, when we say that in toss- ing a coin, the probability of its coming up "heads" is 1/2, we usually mean that in a large number of tosses, about 1/2 of the tosses will come up heads. Unfortunately, relative frequency of occurrence has proved to be an unsatis- factory starting point in defining probability. Although there have been attempts to make frequency of occurrence part of the axiomatic structure of probability theory, the currently accepted formu1ation is one based on measure theory due to Ko1mogorov. In this formulation frequency of occurrence is an interpretation for probability rather than adefinition. This inter- pretation is justified under suitab1e conditions by the 1aw of 1arge numbers. The starting point of probability theory is usua11y taken to be an experi- ment the outcome of which is not fixed apriori. Some fami1iar examples inc1ude tossing a die, observation of a noise vo1tage at a fixed time, the error in measuring a physica1 parameter, and the exact touchdown time of an aircraft.Let ~ denote the set of all possib1e outcomes of an experiment. For examp1e, for the experiment of tossing one die, ~ = {1, 2, 3, 4, 5, 6}, whi1e for the touchdown time of an aircraft, ~ might be chosen to be 0 ~ t < 00. We note that for a given experiment on1y one outcome is ever observed.

This book is a revision of Stochastic Processes in Information and Dynamical Systems written by the first author (E.W.) and published in 1971. The book was originally written, and revised, to provide a graduate level text in stochastic processes for students whose primary interest is its applications. It treats both the traditional topic of sta­ tionary processes in linear time-invariant systems as well as the more modern theory of stochastic systems in which dynamic structure plays a profound role. Our aim is to provide a high-level, yet readily acces­ sible, treatment of those topics in the theory of continuous-parameter stochastic processes that are important in the analysis of information and dynamical systems. The theory of stochastic processes can easily become abstract. In dealing with it from an applied point of view, we have found it difficult to decide on the appropriate level of rigor. We intend to provide just enough mathematical machinery so that important results can be stated PREFACE vi with precision and clarity; so much ofthe theory of stochastic processes is inherently simple if the suitable framework is provided. The price of providing this framework seems worth paying even though the ul­ timate goal is in applications and not the mathematics per se.

This book is a revision of Stochastic Processes in Information and Dynamical Systems written by the first author (E.W.) and published in 1971. The book was originally written, and revised, to provide a graduate level text in stochastic processes for students whose primary interest is its applications. It treats both the traditional topic of sta­ tionary processes in linear time-invariant systems as well as the more modern theory of stochastic systems in which dynamic structure plays a profound role. Our aim is to provide a high-level, yet readily acces­ sible, treatment of those topics in the theory of continuous-parameter stochastic processes that are important in the analysis of information and dynamical systems. The theory of stochastic processes can easily become abstract. In dealing with it from an applied point of view, we have found it difficult to decide on the appropriate level of rigor. We intend to provide just enough mathematical machinery so that important results can be stated PREFACE vi with precision and clarity; so much ofthe theory of stochastic processes is inherently simple if the suitable framework is provided. The price of providing this framework seems worth paying even though the ul­ timate goal is in applications and not the mathematics per se.