MATLAB (Matrix Laboratory)

BPSK Modulation can be done by using a multiplier. Digital data must be multiplied with the carrier frequency. In matlab simulink use a multiplier block to one input apply a sinusoidal generator & to the other a Pulse generator

3D get it!

No, an image formed in a mirror is unreal, because mirror reflects all the light rays off.

the gaussian filter is also known as Gaussian smoothing and is the result of blurring an image by a Gaussian function.

Below code generates unit step function

n1=-4;

n2=5;

n0=0;

[y,n]=stepseq(n0,n1,n2);

stem(n,y);

xlabel('n')

ylabel('amplitude');

title('unit step');

It results in a unit step whose value is 1 for time T>0.

Without image acquisition you have no image to process.

y^2=x^3-x+6

Yes.

Let us use an example:

x=1:10; % Data Set

z=1:20; % Range

y=x^2; % Equation

equation1=trapz(y,z) % This will integrate y over the range of z for your data

When integrating over a matrix:

x2=[ 1 2 3; 4 5 6]; % Matrix

y2=x*C; % Where c is any variable

equation2=trapz(y2);

% Will integrate over every column of your matrix and give you an array.

To read the value of a resistor:

Resistors are color coded, you can use the chart found below

And how accurate the values of resistors are is their tolerance, also found in the chart

Already saved file i.e, .PNG. Open the Photoshop Application , then go to file menu, and select the OPen, where u already saved file is .PNG select it click ok. it will in photoshop file .PNG the again go to file menu then click save as option the name it and format it as .GIF and click it save button.

It depends on the image editor. In Photoshop there's a option of "Place" under the "File" menu. Copy and paste sometimes works or drag and drop from a Windows Explorer (e.g. My Documents) window.

A=2; t = 0:0.0005:1;

x=A*sawtooth(2*pi*5*t,0.25); %5 Hertz wave with duty cycle 25%

plot(t,x);

grid

axis([0 1 -3 3]);

The above code can generate sine wave using Matlab.

/* Discrete Fourier Transform and Power Spectrum Calculates Power Spectrum from a Time Series Copyright 1985 Nicholas B. Tufillaro */ #include #include #define PI (3.1415926536) #define SIZE 512 double ts[SIZE], A[SIZE], B[SIZE], P[SIZE]; main() { int i, k, p, N, L; double avg, y, sum, psmax; /* read in and scale data points */ i = 0; while(scanf("%lf", &y) != EOF) { ts[i] = y/1000.0; i += 1; } /* get rid of last point and make sure # of data points is even */ if((i%2) == 0) i -= 2; else i -= 1; L = i; N = L/2; /* subtract out dc component from time series */ for(i = 0, avg = 0; i < L; ++i) { avg += ts[i]; } avg = avg/L; /* now subtract out the mean value from the time series */ for(i = 0; i < L; ++i) { ts[i] = ts[i] - avg; } /* o.k. guys, ready to do Fourier transform */ /* first do cosine series */ for(k = 0; k <= N; ++k) { for(p = 0, sum = 0; p < 2*N; ++p) { sum += ts[p]*cos(PI*k*p/N); } A[k] = sum/N; } /* now do sine series */ for(k = 0; k < N; ++k) { for(p = 0, sum = 0; p < 2*N; ++p) { sum += ts[p]*sin(PI*k*p/N); } B[k] = sum/N; } /* lastly, calculate the power spectrum */ for(i = 0; i <= N; ++i) { P[i] = sqrt(A[i]*A[i]+B[i]*B[i]); } /* find the maximum of the power spectrum to normalize */ for(i = 0, psmax = 0; i <= N; ++i) { if(P[i] > psmax) psmax = P[i]; } for(i = 0; i <= N; ++i) { P[i] = P[i]/psmax; } /* o.k., print out the results: k, P(k) */ for(k = 0; k <= N; ++k) { printf("%d %g\n", k, P[k]); } }

no way... use awgn function in matlab

There is various line coding schemes that can be used in Matlab including Manchester, polar, unipolar, and bipolar. The Matlab language allows you to write these codes in math-based notations making it easy to see solutions.

matlab code for convolutional coding and BCH coding

d = det(X) returns the determinant of the square matrix X. If X contains only integer entries, the result d is also an integer.

The determinant is computed from the triangular factors obtained by Gaussian elimination [L,U] = lu(A)

s = det(L) % This is always +1 or -1

det(A) = s*prod(diag(U))

The statement A = [1 2 3; 4 5 6; 7 8 9]

produces A =

1 2 3

4 5 6

7 8 9

This happens to be a singular matrix, so d = det(A) produces d = 0. Changing A(3,3) with A(3,3) = 0 turns A into a nonsingular matrix. Now d = det(A) produces d = 27.

For more info visit

http://www.mathworks.com/access/helpdesk/help/techdoc/ref/det.html

significance of abc-dq conversion

Autonomous = done automatically by a software (used in robotics)

Image segmentation = dividing the image into parts that can be used later to recognize relevant image features (like objects)

The definition of autonomous segmentation is summing up both terms and refers to a automatic, without human intervention, segmentation of the image. It means that the segmentation algorithms auto-calibrate themselves. This may seem a simple task for a controlled indoor environment, but can also become a huge complexity in outdoor scenes where the lightning conditions are ranging from complete darkness to direct sunlight on the sensor.

Not sure what you mean by "clutter". You can simplify your windows down to just the command window by toggling all of them off under the "windows" toolbar.

The way I am doing it now, but this time you cannot tell anyone what this means.

You could get a free license version of MATLAB such as Octave or FreeMat. You can find it very easily by a WWW search. Personally I do use MATLAB from the Mathworks, although you would have to purchase it from the Mathworks. Octave and FreeMat are essentially the same as MATLAB, except a few differences in syntax. If you are a student, you could purchase it at a low cost from the Mathworks. It is slick and simple to get into, and I think worth the cost.