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45 Threads found on edaboard.com: Probability And Random
The trap / detrap process is very long timescale. So the areal effect on trapping would be frequency (still lowish, still random) and not the amplitude of any individual event. I think the probability of time-coincident detraps is very very low. I'd say area moves the voltage amplitude down, and the frequency axis to the (...)
The commulative density function CDF of Rayleigh is given by: Pr(r ≤R)=1-exp(-R^2/2σ^2) What is the probability of getting the value of random variable exactly equal to r?
'morning guang4243, I've applied the technique described in the (brilliant!) book "Numerical Recipes in C" to create random numbers with arbitrary probability distributions with success in the past. The book is available freely on the web, and the section describing both the technique and the generation of Gaussian (...)
The joint pdf of random variables X and Y is fx,y(x,y) = ? 0and fy(y). 2. Find the conditional pdf?s fx|y(x|y) and fy|x(y|x). 3. Are X (...)
Since random noise is in-determinant, you can not calculate the error for 1 bit. You can only say the probability of error. In the 80's we could predict Soft BER and Hard BER on magnetic HDD's using 1 full track of 10KB ( don't laugh) and with delay-lines reduce the window of data recovery top measure margin (...)
I do not understand your Case A. In Gaussian random processes there is a mean value, a standard deviation value and the probability of outcomes can be calculated (likely outcomes above a value, likely outcomes between value....) In uniform distributions there is no mean value and the (...)
4) you have a 3x1 vector x of three i.i.d. Gaussian random variables. you have a matrix A which is k x 3, where k=2, 3, 4, and in all cases the coefficients of A are such that its rank is the minimum between k and 3. Write the joint p.d.f. of y=Ax for al the values of k. (Note: k=2,3 are easy but k=4 requires some thought)
I'm deriving equations, and I'm stuck at the following. +inf ∫ dN = ? -inf where N: random variable,pdf: Gaussian probability distribution function. Can we express the above equation without pdf(N) or whatever we can derive? Thanks,
Hi pakitos, use rand() function. It returns random numbers uniformly distributed between 0 and 1. Let x=rand(1); The probability that x is between 0 and p is p (p between 0 and 1); The probability that x is between p1 and p2 is p2-p1 (...)
Hello. I made a modulator-demodulator binary PAM in a pair of FPGAs. Now, I want to test my design to find the bit error rate (or error probability) versus SNR. What is a correct procedure to achive a good estimation of the BER? my method, at this time was the following. I generated 100 random sequences of ones and zeros, I take (...)
I want to send a simple signal s(t) from transmitter to receiver side we get s(t)+n(t) . For this i want convolution of two signal and i want to find out pdf for the convolved sequence. I am getting diffculty in representation of s(t) and n(t) mathametically and also i want inputs. please help me.
In general such problems may be caused by (in decreasing order of probability) a) a bug in the code b) a misunderstanding of how FDTD is set up c) cosmic rays flipping random bits In your case it is a) for i = 100, and j = 80,..120 you let the god of randomness decide the conductivity in your (...)
Hi Please give a link to the solution manual of probability and random processes for electrical engineering Thanks in advance
Request: Any one having the solution manual for the book probability and Random Processess with applications to signal processing by H. Stark and JW Woods Thank you very much
probability, Random Signals, and Statistics X. Rong Li ISBN-10: 0849304334 ISBN-13: 978-0849304330
I want to simulate a periodogram of a smoothed and averaged periodogram. For that, I need the probability distribution of a such periodogram. The averaged periodogram is a random variable of a Gamma distribution with parameters N (the number of averaged periodograms) and S(f)/N (S(f) is the PSD of the signal). The (...)
Your problem comes from a simple model y=x+z, where z has a probability density function with the form f(z)=kexp(-|z|/2) and the underlying assumption is that x and z are two independent random variables, you will get the resulting probability density function for y as you stated. With above (...)
My simulator doesn't support Monte Carlo analysis as Cadence. However it allows sweeping parameter values that are chosen based on statistical variations. For example, it can vary the threshold voltage VTH using random values chosen by probability distribution. The user provides the central value of VTH and its relative variation (as (...)
my friends, Hi i would appreciate if you cloud upload this book as a soft copy. "probability and Random Processes for Electrical Engineering, By Alberto Leon-Garcia " thank you.
u may find it here. probability and Random Processes for Electrical Engineering by Garcia Solution Manual | Solution Manuals for All