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Erhaltene "Hilfreich"-Stimmen für Rezensionen: 91% (29 von 32)
Ort: Los Angeles, CA
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I'm interested in numerical approximation and functional analysis, especially in signal processing and optimization. As an engineer working in industry, my book reviews reflect the point of view of someone who had to teach himself advanced math in the pursuit of solving real problems.
 

Rezensionen

Top-Rezensenten Rang: 3.612.055 - Hilfreiche Stimmen insgesamt: 29 von 32
Introduction to the Theory of Random Processes (Do&hellip von I. I. Gikhman
0 von 1 Kunden fanden die folgende Rezension hilfreich
Although this claims to be an introductory text, it is more like a collection of results in stochastic processes. The notation is often impenetrable and there is not a uniform level of rigor in the text. Some results are presented in detail, and others sort of assume you've seen them before. There is no unifying theme here. It's hard to know where the author is going. A better rigorous book is "Stochastic Processes" by Doob.
Distribution Theory and Transform Analysis: An Int&hellip von Armen H. Zemanian
1 von 1 Kunden fanden die folgende Rezension hilfreich
This is a good second or third book on generalized functions which are otherwise known as "distributions". A good first book is "Fourier Analysis and Generalised Functions" by Lighthill. This book is based on a graduate course and provides a good introduction to distribution theory and generalized Fourier analysis. You need to have a good background in advanced calculus and be comfortable with Lebesgue theorems concerning interchangeable limit processes. The examples are quite good, but the notation is intense and the way that it is packed in small font onto a page doesn't help. The writing is compact and thorough.
I recommend this book to anyone who… Mehr dazu
Fifty challenging problems in probability with sol&hellip von Frederick Mosteller
12 von 14 Kunden fanden die folgende Rezension hilfreich
Excellent selection of problems and very explanatory and detailed solutions. This gets to the ideas behind many of the popular methods in probability, like maximum likelihood. The concepts are given centerstage and provide insights on "how to think" about many problems in probability.