This course has no required or recommended text. However, the optional reference text (A. Papoulis, *Probability, Random Variables, and Stochastic Processes,* McGraw-Hill, third ed., 1991, ISBN: 0070484686) can be used as a supplement to the course notes. This book covers many of the same topics we will, but overwhelming student opinion in the past has been that the book is one they tend to refer to much more after the course than during it for a variety of reasons. While you may well find this book a useful addition to your personal library, we will not assume you have access to the book during the term. Several other texts which may be a useful resource to you are listed below.

### Reference Texts

Anderson, B. D. O., and J. B. Moore. *Optimal Filtering.* Prentice-Hall, 1979. ISBN: 0-13-638122-7 (Out of Print).

Very readable treatment of Kalman and Wiener filtering.

Drake, A.*Fundamentals of Applied Probability Theory.* McGraw-Hill, 1967. ISBN: 0-07-017815-1 (Out of Print).

Basic engineering text on probability theory.

Feller, W. *An Introduction to Probability Theory and Its Applications.* Vols. 1 and 2. Wiley, 1968. ISBN: 0-471-25708-7.

Valuable formal reference set on probability theory.

Gardner, W. A. *Introduction to Random Processes: with Applications to Signals and Systems.* 2nd ed. McGraw-Hill, 1990. ISBN: 0-07-022855-8.

Useful auxilliary reference for a number of topics covered in the course, particularly stochastic processes.

Gray, R. M., and L. D. Davisson. *Random Processes: A Mathematical Approach for Engineers.* Prentice-Hall, 1986. ISBN: 0-13-752882-5 (Out of Print).

Bridges the gap between formal mathematical texts and engineering texts on probability theory.

Helstrom, C. W. *Probability and Stochastic Processes for Engineers.* Macmillan, 1991. ISBN: 0-02-353571-7.

Nice undergraduate level introduction to several themes in the course.

Kay, S. M. *Fundamentals of Statistical Signal Processing and Estimation Theory.* Prentice-Hall, 1993. ISBN: 0-13-345711-7.

Accessible and thorough treatment of estimation theory.

Lee, E., and D. G. Messerschmitt. *Digital Communication.* 2nd ed. Kluwer Academic, 1994. ISBN: 0-89838-274-2.

Advanced reading on applications in communication theory.

Loève, M. *Probability Theory.* Vol. 1. 4th ed. Springer-Verlag, 1977. ISBN: 3-540-90210.

Formal but reasonably readable treatment of probability theory. A classic.

Naylor, A. W., and G. R. Sell. *Linear Operator Theory in Engineering and Science.* Springer-Verlag, 1982. ISBN: 0-387-90748-3 (Out of Print).

Accessible treatment of the mathematical foundations for vector space concepts.

Oppenheim, A. V., and R. W. Schafer. *Discrete-Time Signal Processing.* Prentice Hall, 1989. ISBN: 0-13-216292-X (Out of Print).

Standard text on discrete-time linear systems and signals.

Oppenheim, A. V., and A. S. Willsky. *Signals and Systems.* Prentice-Hall, 1982. ISBN: 0-13-814757-4.

Standard undergraduate text on signals and systems.

Parzen, E. *Stochastic Processes.* Holden-Day, 1962. ISBN: 0-8162-6664-6.

Classic, formal text on stochastic processes.

Scharf, L. L. *Statistical Signal Processing: Detection, Estimation, and Time Series Analysis*. Addison-Wesley, 1991. ISBN: 0-201-19038-9.

Slightly more advanced treatment of several detection and estimation topics.

Stark, H., and J. W. Woods. *Probability, Random Processes, and Estimation Theory for Engineers*. 2nd ed. Prentice-Hall, 1994. ISBN: 0-13-728791-7 (Out of Print).

A useful reference for many topics in the course, as well as the background material.

Strang, G.*Linear Algebra and its Applications*. 3rd ed. Harcourt Brace Jovanovich, 1988. ISBN: 0-15-551006-1.

Standard reference text on linear algebra.

Therrien, C. W. *Discrete Random Signals and Statistical Signal Processing.* Prentice-Hall, 1992. ISBN: 0-13-852112-3 (Out of Print).

Very accessible reference for many topics in the course.

Van, H. L. *Trees, Detection, Estimation and Modulation Theory, Part I.* Wiley, 1968. ISBN: 0-471-89955-0 (Out of Print).

Classic and valuable reference text on detection and estimation theory.