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Nonlinear Regression Analysis and Its Applications
Provides a presentation of the theoretical, practical, and computational aspects of nonlinear regression. There is background material on linear regression, including a geometrical development for linear and nonlinear least squares.
Professor Donald W. Watts Papers
Newspaper cuttings and speeches.
Air Force Register
None
Computing Science and Statistics
Interface '90 is the continuation of an ext!remely successful symposium series. The series has provided a forum for the interaction of professionals in statistics, computing science, and in numerical methods, wherein they may discuss a wide range of topics at the interface of these disciplines. This, the 22nd Symposium on the Interface: Computing Science and Statistics, was held 16-19 May, 1990 at the Kellogg Center on the campus of Michigan State University and is the third Symposium to be held under the recently organized Interface Foundation of North America. The Interface Board of Directors consists of the nine most recent Symposium Chairs: James E. Gentle, Lynne Billard, David M. Allen,...
Machine and Deep Learning Algorithms and Applications
This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of machine learning that involves extensive use of layers of artificial neural networks typically trained on massive amounts of data. Machine and deep learning methods are often used in contemporary data science tasks to address the growing data sets a...
USA Trade World
None
Signal Processing
Signal processing arises in the design of such diverse systems as communications, sonar, radar, electrooptical, navigation, electronic warfare and medical imaging systems. It is also used in many physical sciences, such as geophysics, acoustics, and meteorology, among many others. The common theme is to extract and estimate the desired signals, which are mixed with a variety of noise sources and disturbances. Signal processing involves system analysis, random processes, statistical inferences, and software and hardware implementation. The purpose of this book is to provide an elementary, informal introduction, as well as a comprehensive account of principles of random signal processing, with...
