Wireless Monitoring Tools: Netstumbler, WirlessMon, InSSider

Wireless Monitoring

A monitor that does not require a wired connection to the computer system. The first wireless monitors are expected to be released in mid-2008 using wireless USB. To work, a wireless monitor must first packetize the graphics information so that it can be sent over a standard USB connection; then, a wireless USB transmitter picks it up and sends it; and finally, a receiver on the monitor takes in that data and converts it back into graphic pixels. Wireless monitors offer two basic configurations: adapter sets that let customers transform their existing displays, or monitors with wireless connectivity built-in.

Parameter Description

RSSI :- Receive signal strength indicator of the client RF session.

SNR :- Signal to noise ratio of the client RF session.

Bytes Sent and Received :- Total number of bytes sent to the client and received by the controller from the client.

Packets Sent and Received :- Total number of packets sent to the client and received by the controller from the client.

Client RSSI History (dBm) :- History of RSSI as detected by the access point with which the client is associated.

Client SNR History :- History of SNR as detected by the access point with which the client is associated. 

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Write a MATLAB code to decode all the received words for (n,k) linear block code

MATLAB CODE:

clc;

clear all;

close all;

n=input('enter the code digits');

k=input('enter the data digits');

p=input('enter the parity matrix it must bei k rows and m coloums'); disp(p)

z=input('enter 1 for systmetic and 0 for nonsystmetic');

msg=[];

for i=0:2^k-1

    msg=[msg;de2bi(i,k,'left-msb')];

end

if z==1

  %p=[1 0 1;0 1 1;1 1 0];

  i=eye([k k])

  g=[i p]

else

  g=input('enter the generator matrix in k*n '); 

end   

code =rem(msg*g,2)

decmsg=decode(code ,n,k,'linear',g)

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MATLAB code to plot the capacity of band limited AWGN channel with input constraint S and bandwidth B given by C=B log (1+S/N)

code:

    clc;

    s=input('enter signal power');

    w=input('enter the value of white power per unit bandwidth');

    b=0:0.1:100;

    d=w.*b;

    e=s./d;

    c=b.*log2(1+e);

    plot(b,c);

    xlabel('Bandwidth --->');

    ylabel('Capicaty--->');

    grid;

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implementation of Naive Bayes classifier using excel

Implementation of Naive Bayes classifier using excel:

I have created a excel sheet . it is given below. You can download it.  There is one predefined data set is given and based on that using  naive Bayes classifier you can predict that play can be possible or not.

click here to download the excel file..!!!!!!

Snapshot of the output:

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