From 1972 to 1975, he was with Bell Laboratories, Holmdel, NJ, where he was involved with transmission planning for speech communications and simulation and subjective testing of speech processing algorithms.

From 1975 to 1977, he attended Georgia Institute of Technology to study communication theory and digital signal processing. From 1977 to 1980, he was with the Submarine Signal Division, Portsmouth, RI, where he engaged in research on autoregressive spectral estimation and the design of sonar systems. He is presently a Professor of Electrical Engineering at the University of Rhode Island, Kingston, and a consultant to numerous industrial concerns, the Air Force, the Army, and the Navy.

As a leading expert in statistical signal processing, he has been invited to teach short courses to scientists and engineers at government laboratories, including NASA and the CIA. He has written numerous journal and conference papers and is a contributor to several edited books. He is the author of the textbooks Modern Spectral Estimation (Prentice-Hall, 1988), Fundamentals of Statistical Signal Processing, Vol. I: Estimation Theory (Prentice-Hall, 1993), Fundamentals of Statistical Signal Processing, Vol. II: Detection Theory (Prentice-Hall, 1998), and Intuitive Probability and Random Processes using MATLAB (Springer, 2005).  His current interests are spectrum analysis, detection and estimation theory, and statistical signal processing.

Dr. Kay is a Fellow of the IEEE, and a member of Tau Beta Pi and Sigma Xi. He has been a distinguished lecturer for the IEEE signal processing society. He has been an associate editor for the IEEE Signal Processing Letters and the IEEE Transactions on Signal Processing. He has received the IEEE signal processing society education award “for outstanding contributions in education and in writing scholarly books and texts...”

Dr. Kay has recently been included on a list of the 250 most cited researchers in the world in engineering.

Introduction

Part 1. Methodology and General Approaches

1. Overall Approach With Block Diagram Roadmap

2. Mathematical Modeling

3. General Methods, Assumptions, and Performance

4. Testing and Evaluation

Part 2. Specific Problems and Methods

5. Solving Estimation Problems

6. Solving Detection Problems

7. Doing Spectral Analysis

Part 3. Real-World Case Studies

8. Radar/Sonar

9. Biomedical

10. Communications

Part 4. Some Extensions Required in Practice

11. Continuous Signals

12. Multivariate or Multichannel

13. Two-Dimensional Signals

14. Complex Signals

Appendices

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