Posts 11 - 20 of 27

다음에 대한 결과: 2017

C^5, Cleve’s Corner Collection Card Catalog 2

I have been writing books, programs, newsletter columns and blogs since 1990. I have now collected all of this material into one repository. Cleve's Corner Collection consists of 458 "documents", all available on the internet. There are... 더 읽어보기 >>

Levenshtein Edit Distance Between Strings

How can you measure the distance between two words? How can you find the closest match to a word in a list of words? The Levenshtein distance between two strings is the number of single character deletions, insertions, or substitutions required to transform one string into the other. This is also known as the edit distance.... 더 읽어보기 >>

Latent Semantic Indexing, SVD, and Zipf’s Law 5

Latent Semantic Indexing, LSI, uses the Singular Value Decomposition of a term-by-document matrix to represent the information in the documents in a manner that facilitates responding to queries and other information retrieval tasks. I set out to learn for myself how LSI is implemented. I am finding that it is harder than I thought.... 더 읽어보기 >>

What is the Condition Number of a Matrix? 1

A couple of questions in comments on recent blog posts have prompted me to discuss matrix condition numbers.... 더 읽어보기 >>

Householder Seminar HHXX on Numerical Linear Algebra 2

The Householder meetings on Numerical Linear Algebra have been held roughly every three years since 1961. The twentieth, with the logo HHXX, was held June 18th through 23rd at Virginia Tech in Blacksburg, Virginia. I've been to 17 of the meetings. They have been an important part of my professional life and I've written Cleve's Corner articles and blog posts about them, MathWorks News & Notes, and Householder XIX.... 더 읽어보기 >>

Hilbert Matrices 6

I first encountered the Hilbert matrix when I was doing individual studies under Professor John Todd at Caltech in 1960. It has been part of my professional life ever since.... 더 읽어보기 >>

Quadruple Precision, 128-bit Floating Point Arithmetic 9

The floating point arithmetic format that occupies 128 bits of storage is known as binary128 or quadruple precision. This blog post describes an implementation of quadruple precision programmed entirely in the MATLAB language.... 더 읽어보기 >>

“Half Precision” 16-bit Floating Point Arithmetic 5

The floating point arithmetic format that requires only 16 bits of storage is becoming increasingly popular. Also known as half precision or binary16, the format is useful when memory is a scarce resource.... 더 읽어보기 >>

A Roman Numeral Object, with Arithmetic, Matrices and a Clock 3

A MATLAB object for arithmetic with Roman numerals provides an example of object oriented programming. I had originally intended this as my April Fools post, but I got fascinated and decided to make it the subject of a legitimate article.... 더 읽어보기 >>

Bank Format and Metric Socket Wrenches 2

A report about a possible bug in format bank and a visit to a local hardware store made me realize that doing decimal arithmetic with binary floating point numbers is like tightening a European bolt with an American socket wrench.... 더 읽어보기 >>

Posts 11 - 20 of 27