On estimation of entropy and mutual information of continuous distributions

R. Moddemeijer

doi:10.1016/0165-1684(89)90132-1

On estimation of entropy and mutual information of continuous distributions

R. Moddemeijer

Research output: Contribution to journal › Article › Academic

279 Citations (Scopus)

1667 Downloads (Pure)

Abstract

Mutual information is used in a procedure to estimate time-delays between recordings of electroencephalogram (EEG) signals originating from epileptic animals and patients. We present a simple and reliable histogram-based method to estimate mutual information. The accuracies of this mutual information estimator and of a similar entropy estimator are discussed. The bias and variance calculations presented can also be applied to discrete valued systems. Finally, we present some simulation results, which are compared with earlier work.

Original language	Undefined
Pages (from-to)	233-248
Journal	Signal processing
Volume	16
Issue number	3
DOIs	https://doi.org/10.1016/0165-1684(89)90132-1
Publication status	Published - 1989

Keywords

estimator
variance
bias
IR-70412
Mutual information
Entropy
Delay estimation

Access to Document

10.1016/0165-1684(89)90132-1

Moddemeijer89on

Cite this

@article{9aa201073dc642f2ad00a6849e0da465,

title = "On estimation of entropy and mutual information of continuous distributions",

abstract = "Mutual information is used in a procedure to estimate time-delays between recordings of electroencephalogram (EEG) signals originating from epileptic animals and patients. We present a simple and reliable histogram-based method to estimate mutual information. The accuracies of this mutual information estimator and of a similar entropy estimator are discussed. The bias and variance calculations presented can also be applied to discrete valued systems. Finally, we present some simulation results, which are compared with earlier work.",

keywords = "estimator, variance, bias, IR-70412, Mutual information, Entropy, Delay estimation",

author = "R. Moddemeijer",

year = "1989",

doi = "10.1016/0165-1684(89)90132-1",

language = "Undefined",

volume = "16",

pages = "233--248",

journal = "Signal processing",

issn = "0165-1684",

publisher = "Elsevier B.V.",

number = "3",

}

TY - JOUR

T1 - On estimation of entropy and mutual information of continuous distributions

AU - Moddemeijer, R.

PY - 1989

Y1 - 1989

N2 - Mutual information is used in a procedure to estimate time-delays between recordings of electroencephalogram (EEG) signals originating from epileptic animals and patients. We present a simple and reliable histogram-based method to estimate mutual information. The accuracies of this mutual information estimator and of a similar entropy estimator are discussed. The bias and variance calculations presented can also be applied to discrete valued systems. Finally, we present some simulation results, which are compared with earlier work.

AB - Mutual information is used in a procedure to estimate time-delays between recordings of electroencephalogram (EEG) signals originating from epileptic animals and patients. We present a simple and reliable histogram-based method to estimate mutual information. The accuracies of this mutual information estimator and of a similar entropy estimator are discussed. The bias and variance calculations presented can also be applied to discrete valued systems. Finally, we present some simulation results, which are compared with earlier work.

KW - estimator

KW - variance

KW - bias

KW - IR-70412

KW - Mutual information

KW - Entropy

KW - Delay estimation

U2 - 10.1016/0165-1684(89)90132-1

DO - 10.1016/0165-1684(89)90132-1

M3 - Article

SN - 0165-1684

VL - 16

SP - 233

EP - 248

JO - Signal processing

JF - Signal processing

IS - 3

ER -