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`include "SD_defines.v" module SD_FIFO_RX_FILLER ( input clk, input rst, //WB Signals output [31:0] m_wb_adr_o, output reg m_wb_we_o, output reg [31:0] m_wb_dat_o, output r

`include "SD_defines.v" //------------------------- //------------------------- module CMD_SERIAL_HOST ( SD_CLK_IN, RST_IN, SETTING_IN,GO_IDLE ,CMD_IN, REQ_IN, ACK_OUT, REQ_OUT,ACK_IN, CMD_OUT, STA

`include "SD_defines.v" module SD_FIFO_TX_FILLER ( input clk, input rst, //WB Signals output [31:0] m_wb_adr_o, output reg m_wb_we_o, input [31:0] m_wb_dat_i, output reg m_wb_c

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

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 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

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 %

clear all, clc; ft = 1200; %耔沩嚯 fd=32e3; %鬣耱铗