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choicegroupdemo.java
/*
* %W% %E%
*
* Copyright (c) 2000-2002 Sun Microsystems, Inc. All rights reserved.
* PROPRIETARY/CONFIDENTIAL
* Use is subject to license terms
*/
package choicegroup;
import javax.microedit
noninteractivegaugerunnable.java
/*
* %W% %E%
*
* Copyright (c) 2000-2002 Sun Microsystems, Inc. All rights reserved.
* PROPRIETARY/CONFIDENTIAL
* Use is subject to license terms
*/
package gauge;
import javax.microedition.lc
incrementalindefinitegaugerunnable.java
/*
* %W% %E%
*
* Copyright (c) 2000-2002 Sun Microsystems, Inc. All rights reserved.
* PROPRIETARY/CONFIDENTIAL
* Use is subject to license terms
*/
package gauge;
import javax.microedition.lc
gaugedemo.java
/*
* %W% %E%
*
* Copyright (c) 2000-2002 Sun Microsystems, Inc. All rights reserved.
* PROPRIETARY/CONFIDENTIAL
* Use is subject to license terms
*/
package gauge;
import javax.microedition.lc
alertdemo.java
/*
* %W% %E%
*
* Copyright (c) 2000-2002 Sun Microsystems, Inc. All rights reserved.
* PROPRIETARY/CONFIDENTIAL
* Use is subject to license terms
*/
package alert;
import javax.microedition.lc
textboxdemo.java
/*
* %W% %E%
*
* Copyright (c) 2000-2002 Sun Microsystems, Inc. All rights reserved.
* PROPRIETARY/CONFIDENTIAL
* Use is subject to license terms
*/
package textbox;
import javax.microedition.
bitgen.rsp
-w
-g DebugBitstream:No
-g Binary:no
-g Gclkdel0:11111
-g Gclkdel1:11111
-g Gclkdel2:11111
-g Gclkdel3:11111
-g ConfigRate:4
-g CclkPin:PullUp
-g M0Pin:PullUp
-g M1Pin:PullUp
-g M2Pin:Pu
bitgen.rsp
-w
-g DebugBitstream:No
-g Binary:no
-g Gclkdel0:11111
-g Gclkdel1:11111
-g Gclkdel2:11111
-g Gclkdel3:11111
-g ConfigRate:4
-g CclkPin:PullUp
-g M0Pin:PullUp
-g M1Pin:PullUp
-g M2Pin:Pu
init_drnlms.m
% [w,x,d,y,e,p]=init_drnlms(L,w0,x0,d0)
%
% Creates and initializes the variables required for the
% Data Reusing Normalized Least Mean Squares algorithm.
%
% Input Parameters [Size]::
%
asptmvsslms.m
% [w,g,mu,y,e]= asptmvsslms(x,w,g,d,mu,roh,mu_min,mu_max)
%
% Performs filtering and coefficient update using the
% Modified Variable Step Size LMS Adaptive algorithm.
%
% Input Parameters