Linear transformation of binary random vectors and its application to approximating probability distributions

Tzay Y. Young; Philip S. Liu

doi:10.1109/TIT.1978.1055866

Linear transformation of binary random vectors and its application to approximating probability distributions

Tzay Y. Young, Philip S. Liu

Electrical & Computer Engineering

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

A nonsingular transformation of binary-valued random vectors y equals xA which minimizes a mutual information criterion I(y) is considered. It is shown that a nonsingular A exists such that I(y) equals 0 if and only if x has a generalized binomial distribution. Computational algorithms for seeking an optimal A are developed, and dimensionality reduction is discussed briefly. This linear transformation is useful in improving the approximation of probability distributions. Numerical examples are presented.

Original language	English (US)
Pages (from-to)	152-156
Number of pages	5
Journal	IEEE Transactions on Information Theory
Volume	24
Issue number	2
DOIs	https://doi.org/10.1109/TIT.1978.1055866
State	Published - Mar 1978

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Library and Information Sciences

Access to Document

10.1109/TIT.1978.1055866

Fingerprint Dive into the research topics of 'Linear transformation of binary random vectors and its application to approximating probability distributions'. Together they form a unique fingerprint.

Cite this

@article{ab4754d507ee4b348a2900ad6532ddf4,

title = "Linear transformation of binary random vectors and its application to approximating probability distributions",

abstract = "A nonsingular transformation of binary-valued random vectors y equals xA which minimizes a mutual information criterion I(y) is considered. It is shown that a nonsingular A exists such that I(y) equals 0 if and only if x has a generalized binomial distribution. Computational algorithms for seeking an optimal A are developed, and dimensionality reduction is discussed briefly. This linear transformation is useful in improving the approximation of probability distributions. Numerical examples are presented.",

author = "Young, {Tzay Y.} and Liu, {Philip S.}",

year = "1978",

month = mar,

doi = "10.1109/TIT.1978.1055866",

language = "English (US)",

volume = "24",

pages = "152--156",

journal = "IEEE Transactions on Information Theory",

issn = "0018-9448",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "2",

}

TY - JOUR

T1 - Linear transformation of binary random vectors and its application to approximating probability distributions

AU - Young, Tzay Y.

AU - Liu, Philip S.

PY - 1978/3

Y1 - 1978/3

N2 - A nonsingular transformation of binary-valued random vectors y equals xA which minimizes a mutual information criterion I(y) is considered. It is shown that a nonsingular A exists such that I(y) equals 0 if and only if x has a generalized binomial distribution. Computational algorithms for seeking an optimal A are developed, and dimensionality reduction is discussed briefly. This linear transformation is useful in improving the approximation of probability distributions. Numerical examples are presented.

AB - A nonsingular transformation of binary-valued random vectors y equals xA which minimizes a mutual information criterion I(y) is considered. It is shown that a nonsingular A exists such that I(y) equals 0 if and only if x has a generalized binomial distribution. Computational algorithms for seeking an optimal A are developed, and dimensionality reduction is discussed briefly. This linear transformation is useful in improving the approximation of probability distributions. Numerical examples are presented.

UR - http://www.scopus.com/inward/record.url?scp=0017946770&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0017946770&partnerID=8YFLogxK

U2 - 10.1109/TIT.1978.1055866

DO - 10.1109/TIT.1978.1055866

M3 - Article

AN - SCOPUS:0017946770

VL - 24

SP - 152

EP - 156

JO - IEEE Transactions on Information Theory

JF - IEEE Transactions on Information Theory

SN - 0018-9448

IS - 2

ER -

Linear transformation of binary random vectors and its application to approximating probability distributions

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Cite this