chnentropy.1

spiht for linux this is used to decod and encode vedio i wich all enjoy

.TH CHNENTROPY 1 "QCCPACK" ""
.SH NAME
chnentropy \- calculate entropy of channel
.SH SYNOPSIS
.B chnentropy
.RB "[\|" \-vo "\|]"
.RB "[\|" \-d
.IR  vector\_dimension "\|]"
.RB "[\|" \-o
.IR  order "\|]"
.I channelfile
.SH OPTIONS
.TP
.BI \-d " vector\_dimension"
Integer.  Dimension of vectors represented by the symbols in the channel.
.TP
.BI \-o " order"
Integer.  Entropy order. Possible values: 1 or 2; default = 1.
.SH DESCRIPTION
.LP
.B chnentropy
prints the entropy of 
.I channelfile 
.RB ( CHN 
format) to 
.BR stdout .  
Option
.B \-o 
gives the order of the entropy calculation.  Valid values are 1 and 2.
If order 1 is specified, the first-order entropy (sometimes called
the zero-order entropy) is calculated as 
.IR H(X(t)) ,
where 
.I X(t)
is the random process represented by the channel.
If order 2 is specified, the second-order conditional entropy,
.IR H(X(t) " | " X(t-1)) ,
is calculated;
this is the average entropy of the current symbol conditioned on the
preceding symbol and gives an estimate of the entropy rate
of a first-order Markov source.
Of course,
.I X(t)
is assumed to be stationary and ergodic.
.LP
If option 
.B \-d 
is given, the entropy is given as bits per vector component (i.e.,
it is the entropy of the channel symbols (first- or second-order)
divided by 
.IR vector\_dimension ).  
Otherwise, the entropy printed is simply the entropy of channel symbols.
For example, the
.B \-d 
option gives a convenient way to calculate the bit rate, in bits per
original source symbol, when the channel corresponds to indices output
from a vector quantizer (see 
.BR vqencode (1)).
.LP
The 
.B \-vo
option indicates that only the value of the entropy is to be printed
(terse output).
.LP
.B chnentropy
uses
.BR QccChannelEntropy (3)
to perform the entropy calculation.
.SH "SEE ALSO"
.BR QccChannelEntropy (3),
.BR vqencode (1),
.BR vqdecode (1),
.BR QccChannel (3),
.BR QccPack (3)

T. M. Cover and J. T. Thomas, 
.IR "Elements of Information Theory" .
New York: John Wiley & Sons, Inc., 1991.

A. Gersho and R. Gray, 
.IR "Vector Quantization and Signal Compression" .
Norwell, MA: Kluwer Academic Publishers, 1992.

.SH AUTHOR
Copyright (C) 1997-2009  James E. Fowler
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