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Linear Programming --- Roundoff errors

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Linear programming --- Roundoff errors --- Programmation linéaire

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If you are working in digital signal processing, control or numerical analysis, you will find this authoritative analysis of quantization noise (roundoff error) invaluable. Do you know where the theory of quantization noise comes from, and under what circumstances it is true? Get answers to these and other important practical questions from expert authors, including the founder of the field and formulator of the theory of quantization noise, Bernard Widrow. The authors describe and analyze uniform quantization, floating-point quantization, and their applications in detail. Key features include: • Analysis of floating point round off • Dither techniques and implementation issues analyzed • Offers heuristic explanations along with rigorous proofs, making it easy to understand 'why' before the mathematical proof is given.

Roundoff errors. --- Roundoff errors --- Error analysis (Mathematics) --- Numerical analysis --- Errors, Theory of --- Instrumental variables (Statistics) --- Mathematical statistics --- Statistics

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Here is a clear exposition of nonparametric smoothing methods for statisticians. The focus is applied rather than theoretical, with a large number of illustrations from different disciplines.

Mathematical statistics --- Smoothing (Statistics) --- Smoothing (Statistics). --- Basic Sciences. Statistics --- Experimental Design. --- 519.5 --- Curve fitting --- Graduation (Statistics) --- Roundoff errors --- Statistics

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Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. This book provides a concise and comprehensive overview of statistical theory and in addition, emphasis is given to the implementation of presented methods in Matlab. All created programs are included in a special toolbox which is an integral part of the book. This toolbox contains many Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard funct

Smoothing (Statistics) --- Kernel functions. --- Functions, Kernel --- Functions of complex variables --- Geometric function theory --- Curve fitting --- Graduation (Statistics) --- Roundoff errors --- Statistics