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function [p_err,gamma_db]=p_e_sd_o(gamma_db_l,gamma_db_h,k,n,d_min) % p_e_sd_o.m Matlab function for computing error probability in % soft-decision decoding of a linear block code %

function nnd12sd2(cmd,arg1) %NND12SD2 Steepest descent backpropagation demonstration #2. % % This demonstration requires the Neural Network Toolbox. % First Version, 8-31-95. %===============

function nnd12sd1(cmd,arg1) %NND12SD1 Steepest descent backpropagation demonstration #1. % % This demonstration requires the Neural Network Toolbox. % First Version, 8-31-95. %===============

function nnd12sd2(cmd,arg1) %NND12SD2 Steepest descent backpropagation demonstration #2. % % This demonstration requires the Neural Network Toolbox. % First Version, 8-31-95. %===============

function nnd12sd1(cmd,arg1) %NND12SD1 Steepest descent backpropagation demonstration #1. % % This demonstration requires the Neural Network Toolbox. % First Version, 8-31-95. %===============

function [p_err,gamma_db]=p_e_sd_o(gamma_db_l,gamma_db_h,k,n,d_min) % p_e_sd_o.m Matlab function for computing error probability in % soft decision decoding of a linear block code %

Dependencies for Project 'SD', Target 'Target 1': (DO NOT MODIFY !) F (.\Startup.s)(0x43D44D0E)(--device DARMP -g --apcs=interwork -I "D:\Keil\ARM\INC\Philips" --list "Startup.lst" --xref -o "Startup

function nnd12sd2(cmd,arg1) %NND12SD2 Steepest descent backpropagation demonstration #2. % % This demonstration requires the Neural Network Toolbox. % $Revision: 1.8 $ % Copyright 1994-2002 PW

function nnd12sd1(cmd,arg1) %NND12SD1 Steepest descent backpropagation demonstration #1. % % This demonstration requires the Neural Network Toolbox. % $Revision: 1.8 $ % Copyright 1994-2002 PW

/* * @(#)Sd.h * @date 2005/12/25 * @version 1.0 * @author Zhou Shangpin. * Copyright 2005 Anyka corporation, Inc. All rights reserved. * ANYKA PROPRIETARY/CONFIDENTIAL. Use is subject to l