Dan Simon, Professor

I spent 14 years in industry before coming to Cleveland State University in 1999. I received a PhD from Syracuse University, an MS from the University of Washington, and a BS from Arizona State University, all in Electrical Engineering. My work experience includes time in the aerospace, automotive, agricultural, biomedical, process control, and software industries. I have lived in Seattle, Syracuse, Los Angeles, Phoenix, and Akron. My research interests include control theory, signal processing, embedded systems, and computer intelligence.

• Curriculum vita
• Publications
• Google Scholar profile
• You can also download my papers, along with many papers by other CSU faculty and students, from EngagedScholarship@CSU
• New (April 2013): Evolutionary Optimization Algorithms: Biologically-Inspired and Population-Based Approaches to Computer Intelligence, John Wiley & Sons, 2013. This book about evolutionary algorithms is written in the same style as my first book. It includes bottom-up, step-by-step explanations of all of the popular (and many of the less popular) algorithms. In addition to simple explanations and pseudo-code listings, the book includes many recent research results, so students who study the book will be in a good position to embark on their own research ventures. The book includes 103 worked examples and 262 end-of-chapter problems. A solution manual is available to course instructors. Matlab code for the computer examples can be downloaded from the book web site. The book is documented with over 700 references, ranging from historical references that are centuries old, to papers published in 2013.
• Optimal State Estimation: Kalman, H-infinity, and Nonlinear Approaches, John Wiley & Sons, 2006. I took everything I learned in the past 20 years about state estimation and wrote it in this book. I like step-by-step explanations, so that is how I wrote the book. I tried to make it clear, but also included recent research results, so it has a nice balance of established technology and cutting-edge research. It includes 89 worked examples, 176 written exercises, and 52 computer exercises. A solutions manual is available to course instructors from the publisher. Matlab code for the 32 computer examples can be downloaded from the book web site. The book is documented with 381 references, ranging from historical references from the 1920s, to papers published in 2006.
• FAQ for Students
• Courses and Other Resources
• The Embedded Control Systems Research Lab (CSU Server)
• The Embedded Control Systems Research Lab (Lab Server)

Research and Matlab Code

• New: Finite Impulse Response Filtering
• Biogeography-Based Optimization
• New: Linearized BBO with Local Search
• BBO for Noisy Fitness Functions
• Distributed BBO
• Markov Analysis of BBO
• Simplified BBO
• Kalman Filtering with State Constraints (Tutorial)
• Correlation Matrix Approximation Using a Majorization Algorithm
• The Optimal Interpolative Net
• Rule Base Reduction for Fuzzy Logic Systems
• Training Radial Basis Neural Networks with the Extended Kalman Filter
• Fuzzy Membership Function Optimization
• Kalman Filtering with State Constraints
• Reduced Order Kalman Filtering
• Kalman Filtering for Fuzzy Dynamic Systems
• Minimax Filtering with State Constraints
• Splines for Data Smoothing and Interpolation
  

I have a web page on my business site where I've written book reviews and tutorial overviews of various technologies. In the following web pages I express various views related to my profession and other matters.

• My Philosophy as a Professor
• Why I am a Christian
• Christianity and Control Theory
• Modern Science and the Bible (PowerPoint, 10.3 MB) (pdf, 5.8 MB) (MS Word, text only, 80 KB)

Department of Electrical and Computer Engineering

Cleveland State University

Last Revised: April 28, 2013