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- ='''1.5 Poisson Process'''= ...left\{ \mathbf{N}\left(t\right),\; t\geq0\right\}</math> is the Poinsson process. The distribution of <math class="inline">\mathbf{N}\left(t\right)</math>5 KB (920 words) - 11:26, 30 November 2010
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- <strong>Digital Systems</strong> = system that can process a ditital signal.<br/> <li>Deterministic vs. random3 KB (532 words) - 06:43, 16 September 2013
- I cannot write the process of this demonstration due to the limited environment to draw integral. In this case, it is sure that we have to utilize the exponential random variable method.1 KB (248 words) - 21:14, 4 October 2008
- The next morning all n prisoners will be lined up, in random order, If anyone does not follow the rules, he is executed and the process5 KB (756 words) - 08:23, 20 May 2013
- What is it? Sampling is a process of measuring a CT signal x(t) at some specific values of time t. Let <math>x(t)\,</math> be a random signal with frequency <math>\omega \,</math>2 KB (367 words) - 11:27, 7 November 2008
- ...dom variable" being observed should be the sum or mean of many independent random variables. (variables need not be iid)(See the PROOF ) undirected graphs (Markov random fields), probabilistic decision trees/models have a number of31 KB (4,832 words) - 18:13, 22 October 2010
- the underlying process that generated the data. The contributions of this special issue cover a wi ...rocedure consists of starting with k groups which each consist of a single random point, and thereafter adding the points one after another to the group whos39 KB (5,715 words) - 10:52, 25 April 2008
- So, our aim would be to move from a given random point on the surface towards the global minimum. The contour plots are ofte ...at every point, is the one that yields minimum expense of energy, and this process is continued until the directional derivative becomes zero, which means tha2 KB (336 words) - 14:53, 16 March 2008
- ...ovides the foundations for the understanding of digital signals and how to process them (photos, songs,etc). If you do the homework and go to class you are fi ...we spend on reviewing 301 material and spend more time on image and random process. -- [[User:xiao1|Yimin Xiao]]17 KB (3,004 words) - 08:11, 15 December 2011
- ...tral density functions. Random processes and response of linear systems to random inputs.<br/><br/> <br/>ii. an ability to model complex families of signals by means of random processes.2 KB (231 words) - 07:20, 4 May 2010
- ...dom variable" being observed should be the sum or mean of many independent random variables. (variables need not be iid)(See the PROOF ) undirected graphs (Markov random fields), probabilistic decision trees/models have a number of31 KB (4,787 words) - 18:21, 22 October 2010
- [[Category:random variables]] *[[ECE 600 Prerequisites Discrete Random Variables|Discrete Random Variables]]1 KB (139 words) - 13:13, 16 November 2010
- ='''1.5 Poisson Process'''= ...left\{ \mathbf{N}\left(t\right),\; t\geq0\right\}</math> is the Poinsson process. The distribution of <math class="inline">\mathbf{N}\left(t\right)</math>5 KB (920 words) - 11:26, 30 November 2010
- ='''1.6 Continuous Random Variables'''= ...tribution, then <math class="inline">\mathbf{Y}=\ln\mathbf{X}</math> is a random variable with Gaussian distribution. This distribution is characterized wit5 KB (843 words) - 11:27, 30 November 2010
- [[Category:random variables]] =Sequences of Random Variables=1 KB (194 words) - 11:35, 30 November 2010
- Stochastic process ...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)</16 KB (2,732 words) - 11:47, 30 November 2010
- ...}_{n},\cdots</math> be a sequence of independent, identically distributed random variables, each having pdf ...ht)}\left(x\right).</math> Let <math class="inline">Y_{n}</math> be a new random variable defined by10 KB (1,713 words) - 07:17, 1 December 2010
- ...inline">\mathbf{X}\left(t,\omega\right)</math> , then we have a new random process <math class="inline">\mathbf{Y}\left(t\right)</math> : <math class="inline" We will assume that <math class="inline">T</math> is deterministic (NOT random). Think of <math class="inline">\mathbf{X}\left(t\right)=\text{input to a s11 KB (1,964 words) - 11:52, 30 November 2010
- The power spectrum or power spectral density (PSD) of a W.S.S. random process <math class="inline">\mathbf{X}\left(t\right)</math> , real or complex, is The PSD gives the average distribution of power in frequency for a random process.3 KB (492 words) - 11:53, 30 November 2010
- ...lass="inline">\mathbf{Y}\left(t\right)</math> be the “smoothed” random process given by <math class="inline">\mathbf{Y}\left(t\right)=\frac{1}{2T}\int_{t- ...be two zero-mean statistically independent, jointly wide-sense stationary random processes. Then the cross-correlation function <math class="inline">R_{\mat3 KB (498 words) - 07:16, 1 December 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
