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- .../vise.www.ecn.purdue.edu/VISE/ee438L/lab1/pdf/lab1.pdf Lab on discrete and continuous signals] ==Random sequences ==8 KB (1,226 words) - 11:40, 1 May 2009
- * For Continuous Random Variable: ==Theorem of Total Probability for Continuous Random Variables==4 KB (722 words) - 13:05, 22 November 2011
- ...r is denoted P(A|X = 0) and the latter P(A|X = 1). Now define a new random variable Y, whose value is P(A|X = 0) if X = 0 and P(A|X = 1) if X = 1. That is ...to be the conditional probability of the event A given the discrete random variable X:2 KB (332 words) - 16:52, 20 October 2008
- <math>f_x(X; \theta)</math> (continuous) <math>P_\theta(\theta)</math> (continuous)4 KB (671 words) - 09:23, 10 May 2013
- == Problem 1: Random Point, Revisited== In the following problems, the random point (X , Y) is uniformly distributed on the shaded region shown.4 KB (703 words) - 12:58, 22 November 2011
- ...dom variable" being observed should be the sum or mean of many independent random variables. (variables need not be iid)(See the PROOF ) ...nly statistical model that is needed is the conditional model of the class variable given the measurement. This conditional model can be obtained from a joint31 KB (4,832 words) - 18:13, 22 October 2010
- ...-j 2 \pi f t} dt</math> <br> A CTFT( continuous time fourier transform) is continuous in both the time and frequency domain. Give example here. ...(samples per second). Then the DTFT provides an approximation of the continuous time Fourier transform.13 KB (2,348 words) - 13:25, 2 December 2011
- ...dom variable" being observed should be the sum or mean of many independent random variables. (variables need not be iid)(See the PROOF ) ...nly statistical model that is needed is the conditional model of the class variable given the measurement. This conditional model can be obtained from a joint31 KB (4,787 words) - 18:21, 22 October 2010
- ='''1.6 Continuous Random Variables'''= ...on, then <math class="inline">\mathbf{Y}=\ln\mathbf{X}</math> is a random variable with Gaussian distribution. This distribution is characterized with two par5 KB (843 words) - 11:27, 30 November 2010
- Given a random sequence <math class="inline">\mathbf{X}_{1}\left(\omega\right),\mathbf{X}_ We say a sequence of random variables converges everywhere (e) if the sequence <math class="inline">\ma10 KB (1,667 words) - 11:37, 30 November 2010
- ...ead of mapping each <math class="inline">\omega\in\mathcal{S}</math> of a random experiment to a number <math class="inline">\mathbf{X}\left(\omega\right)</ ...andom about the sample functions. The randomness comes from the underlying random experiment.16 KB (2,732 words) - 11:47, 30 November 2010
- ...1 dime. One of the boxes is selected at random, and a coin is selected at random from that box. The coin selected is a quater. What is the probability that – A = Box selected at random contains at least one dime.22 KB (3,780 words) - 07:18, 1 December 2010
- ...<math class="inline">q=1-p</math> . Given that a set of twins selected at random are of the same sex, what is the probability they are fraternal? ...h class="inline">\mathbf{X}</math> in a baseball game is a Poisson random variable. If the probability of a no-hit game is 1/3 , what is the probability of ha12 KB (2,205 words) - 07:20, 1 December 2010
- ...irst coin is fair and the second coin has two heads. One coin is picked at random and tossed two times. It shows heads both times. What is the probability th ...mathbf{Y}_{t}</math> by jointly wide sense stationary continous parameter random processes with <math class="inline">E\left[\left|\mathbf{X}\left(0\right)-\9 KB (1,534 words) - 08:33, 27 June 2012
- ...>\mathbf{Y}</math> be two independent identically distributed exponential random variables having mean <math class="inline">\mu</math> . Let <math class="in ...deals with the exponential random variable rather than the Poisson random variable.14 KB (2,358 words) - 08:31, 27 June 2012
- ...th> and <math class="inline">\mathbf{Y}</math> be two joinly distributed random variables having joint pdf Let <math class="inline">\mathbf{Z}</math> be a new random variable defined as <math class="inline">\mathbf{Z}=\mathbf{X}+\mathbf{Y}</math> . F9 KB (1,560 words) - 08:30, 27 June 2012
- =Example. Sequence of binomially distributed random variables= ...omially distributed random variables, with the <math>n_{th}</math> random variable <math>\mathbf{X}_{n}</math> having pmf3 KB (470 words) - 13:02, 23 November 2010
- =Example. Sequence of binomially distributed random variables= ...uted random variables, with the <math class="inline">n_{th}</math> random variable <math class="inline">\mathbf{X}_{n}</math> having pmf3 KB (539 words) - 12:14, 30 November 2010
- ...stem [[Video Tutorial on How to Cascade Transformations of the Independent Variable|cascade]]: <br>x(t) = the amount of protein released by damaged endothelium ...ls require filtering of background noise and, often times, conversion from continuous time (CT) to discrete time (DT).<br>17 KB (2,368 words) - 10:53, 6 May 2012
- *Discrete Random Variables ...02S13Boutin|Normalizing the probability mass function of a discrete random variable]]7 KB (960 words) - 18:17, 23 February 2015
