The mathematical operation of quantization exists in many communication and control systems. The increasing demand on existing digital facilities, such as communication channels and data storage, can be alleviated by representing the same amount of information with fewer bits at the expense of more sophisticated data processing. In Estimation and Control with Quantized Measurements, Dr. Curry examines the two distinct but related problems of state variable estimation and control when the measurements are quantized. Consideration is limited to discrete-time problems, and emphasis is placed on coarsely quantized measurements and linear, possibly time-varying systems.
In addition to examining the development of the fundamental minimum variance or conditional mean estimate, which lays the groundwork for other types of estimates, the author also looks at easier-to-implement approximate nonlinear filters in conjunction with three communication systems, and so the book is not limited to theory alone. Next, the performance of optimum linear estimators is compared with the nonlinear filters.
Along with a new interpretation of the problem of generating estimates from quantized measurements. both optimal and suboptimal stochastic control with quantized measurements are treated for the first time in print by Dr. Curry.