This text discusses the mathematical foundations of statistical inference for building 3-dimensional models from image and sensor data that contain noise — a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. 1996 edition. Slightly corrected republication of the edition published by Elsevier Science, Amsterdam, 1996.
Optimal Filtering by Brian D. O. Anderson, John B. Moore Graduate-level text extends studies of signal processing, particularly regarding communication systems and digital filtering theory. Topics include filtering, linear systems, and estimation; discrete-time Kalman filter; time-invariant filters; more. 1979 edition.
Digital Filters by Richard W. Hamming Introductory text examines role of digital filtering in many applications, particularly computers. Focus on linear signal processing; some consideration of roundoff effects, Kalman filters. Only calculus, some statistics required.
Variational Methods in Optimization by Donald R. Smith Highly readable text elucidates applications of the chain rule of differentiation, integration by parts, parametric curves, line integrals, double integrals, and elementary differential equations. 1974 edition.
