Procedure:-
1) Find the length of the first sequence x=x_length
2) Find the length of the second sequence h=h_length
3) Estimate the number of samples in the result of linear convolution of x &h=Y_length
4) If X_length 5) If h_length 6) Take DFT for modified x=x(k)
7) Take DFT for modified h=H(k)
8) ....etc

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#include
#include
short x;
void dft(short *x, short k, int *out); //function prototype
#define N 8 //number of data values
float pi = 3.1416;
int sumRe,sumIm;
short x = {1,2,3,4,5,6,7,8}; //1-cycle cosine
int out = {0,0};
int real,imag,k=0; //init Re and Im results
void dft(short *x, short k, int *out) //DFT function
{
int sumRe = 0, sumIm = 0; //init real/imag components
float cs = 0, sn = 0; //init cosine/sine components
int i = 0;
for (i = 0; i < N; i++) //for N-point DFT
{
cs = cos(2* ....etc

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Dear Sir,
Can you please provide the code for An improved dft based channel estimation algorithm for mimo ofdm systems, as i have the code but the execution results are not related with the abstract results.
thanks in advance. ....etc

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2-D DFT of two dimensional finite extent sequences.

2-D DFT and Convolution
The DFT can be computed with a fast algorithm and it is sometimes beneficial to do the convolution of two sequences A (M1 £ N1) and B (M2 £ N2) via point DFTs. Speed improvements are only possible if both sequences have large dimensions. Otherwise convolutions are better implemented via the convolution sum.

2-D Low-Pass Filtering of Images We will be intere ....etc

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Procedure:-
1) Find the length of the first sequence x=x_length
2) Find the length of the first sequence h=h_length
3) Take the circular convolution order as N
4) If x_length < N, pad enough number of zeros to x, so that the number of samples in the modified x=N
5) If h_length < N ,pad enough number of zeros to h, so that the number of samples in the modified h=N
6) Take DFT for modified x=x(k)
7) Take DFT for modified h=H(k)
8) Compute Y(K)=X(K)*H(K)
9) Compute y(n)=IDFT(Y(k))
10) Verify if y=conv(x, ....etc

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Abstract
Information hiding for covert communication is rapidlygaining momentum. With sophisticated techniques beingdeveloped in steganography, steganalysis needs to beuniversal. In this paper we propose Universal Steganalysisusing Histogram, Discrete Fourier Transform and SVM(SHDFT). The stego image has irregular statisticalcharacteristics as compare to cover image. Using Histogramand DFT, the statistical features are generated to train One-Class SVM to discriminate the cover and stego image.SHDFT algorithm is found to be efficient an ....etc

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i need mat lab code for an improved dft based channel estimation algorithm for mimo ofdm systems
sent me the mat lab code for an improved dft based channel estimation algorithm for mimo ofdm systems ....etc

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Procedure:-
1) Enter the number of points, N
2) Enter the input sequence elements, x
3) Create a vector for the sample index, ’n’
4) Initialize loop variable, ‘k’ for the DFT samples X(k)
5) Calculate the twiddle factor for each ‘k’
6) Multiply x and the twiddle factors , elements-by-element
7) Sum all the products, assign to X(k)
8) Plot the magnitude and phase spectrum
9) Verify the results with built in function
MATLAB program for DFT
clear
clc
close all
% ENTER THE NUMBER OF POINTS
N = ....etc

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sir i need PPt n report reagarding single point n overlap FFT. if u can helpme it will be great of u. ....etc

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#define PTS 256 //# of points for FFT
typedef struct {float real,imag;} COMPLEX;
extern COMPLEX w; //twiddle constants stored in w

void FFT(COMPLEX *Y, int N) //input sample array, # of points
{
COMPLEX temp1,temp2; //temporary storage variables
int i,j,k; //loop counter variables
int upper_leg, lower_leg; //index of upper/lower butterfly leg
int leg_diff; //difference between upper/lower leg
int num_s ....etc

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