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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
- ...<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? ...ts <math 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 probabil12 KB (2,205 words) - 07:20, 1 December 2010
- ...th> be a sequence of random variables that converge in mean square to the random variable <math class="inline">\mathbf{X}</math> . Does the sequence also co ...> A sequence of random variable that converge in mean square sense to the random variable <math class="inline">\mathbf{X}</math> , also converges in probabi6 KB (1,093 words) - 08:23, 27 June 2012
- Consider the following random experiment: A fair coin is repeatedly tossed until the same outcome (H or T ...math> , respectively. Let <math class="inline">\mathbf{Z}</math> be a new random variable defined as <math class="inline">\mathbf{Z}=\mathbf{X}+\mathbf{Y}.<10 KB (1,827 words) - 08:33, 27 June 2012
- ...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
- ...ft(x\right)=P\left(\left\{ \mathbf{X}\leq x\right\} \right)</math> of the random variable <math class="inline">\mathbf{X}</math> . Make sure and specify you ...inline">\mathbf{Y}</math> is <math class="inline">r</math> . Define a new random variable <math class="inline">\mathbf{Z}</math> by <math class="inline">\m10 KB (1,652 words) - 08:32, 27 June 2012
- ...class="inline">\mathbf{Y}</math> be jointly Gaussian (normal) distributed random variables with mean <math class="inline">0</math> , <math class="inline">E\ ...}</math> . Note: <math class="inline">\mathbf{V}</math> is not a Gaussian random variable.6 KB (916 words) - 08:26, 27 June 2012
- State the definition of a random variable; use notation from your answer in part (a). A random variable <math class="inline">\mathbf{X}</math> is a process of assigning a number <math class="inline">\mathbf{X}\left(\xi\right)</math10 KB (1,608 words) - 08:31, 27 June 2012
- Assume that <math class="inline">\mathcal{S}</math> is the sample space of a random experiment and that <math class="inline">\mathcal{F}_{1}</math> and <math ...<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? (Simplify7 KB (1,210 words) - 08:31, 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 ...that it deals with the exponential random variable rather than the Poisson random variable.14 KB (2,358 words) - 08:31, 27 June 2012
- Assume that <math class="inline">\mathbf{X}</math> is a binomial distributed random variable with probability mass function (pmf) given by <math class="inline" ...dots,\mathbf{X}_{n},\cdots</math> be a sequence of binomially distributed random variables, with <math class="inline">\mathbf{X}_{n}</math> having probabil10 KB (1,754 words) - 08:30, 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}</9 KB (1,560 words) - 08:30, 27 June 2012
- ...of independent, identically distributed zero-mean, unit-variance Gaussian random variables. The sequence <math class="inline">\mathbf{X}_{n}</math> , <math ...les, <math class="inline">\mathbf{X}_{n}</math> is a sequence of Gaussian random variables with zero mean and variance <math class="inline">\sigma_{\mathbf{14 KB (2,439 words) - 08:29, 27 June 2012
- ...ass="inline">\mathbf{Y}</math> be two independent identically distributed random variables taking on values in <math class="inline">\mathbf{N}</math> (the ...y distributed random variables, with the <math class="inline">n</math> -th random variable <math class="inline">\mathbf{X}_{n}</math> having pmf <math class10 KB (1,636 words) - 08:29, 27 June 2012
- ..._{1},\mathbf{X}_{2},\mathbf{X}_{3},\cdots</math> is a sequence of i.i.d. random variables with finite mean <math class="inline">E\left[\mathbf{X}_{i}\right ...hbf{X}_{2},\mathbf{X}_{3},\cdots</math> be a sequence of i.i.d Bernoulli random variables with <math class="inline">p=1/2</math> , and let <math class="inl12 KB (1,920 words) - 08:28, 27 June 2012
- Note that the playing process have two key elements, the rhythm and the melody. One should regard the message has no meaning. It's just a random combination of syllables. People make guesses, and when the first impressio2 KB (347 words) - 05:37, 15 January 2011
- ...ulse response and infinite impulse response digital filters; processing of random signals. Speech processing; vocal tract models and characteristics of the s ...icro-integrated systems; properties of materials for MEMS; microelectronic process modules for design and fabrication. Students will prepare a project report17 KB (2,368 words) - 10:53, 6 May 2012
- *Discrete Random Variables ...on_ECE302S13Boutin|Normalizing the probability mass function of a discrete random variable]]7 KB (960 words) - 18:17, 23 February 2015
- ...ne to errors, I hope the lack of sophistication in my language will render process of PCA understandable(without being entirely inaccurate). Principal Component Analysis is a process of extracting useful information from a noisy data set. Complex data sets m6 KB (1,043 words) - 12:45, 3 March 2015
- ...erent but the general theme is there) and how industry handles the project process (similar to class projects just on a much larger scale). I would say the t ...f our career. They really want to see what else you know- can you talk to random people, are you a team player, can you think on your feet, can you be socia20 KB (3,616 words) - 06:10, 2 September 2013
- ...sphere, which is just the basketball that everyone is familiar with. This process of shrinking a loop is illustrated in the picture below. The Poincaré con ...according to the Poincaré conjecture, what you really have (instead of a random blob of play-doh) is just an out-of-shape ball.9 KB (1,549 words) - 06:55, 21 March 2013
- [[Category:random variables]] Question 1: Probability and Random Processes3 KB (406 words) - 10:19, 13 September 2013
- [[Category:random variables]] Question 1: Probability and Random Processes5 KB (763 words) - 10:57, 10 March 2015
- [[Category:random variables]] Question 1: Probability and Random Processes5 KB (780 words) - 01:25, 9 March 2015
- [[Category:random variables]] Question 1: Probability and Random Processes5 KB (766 words) - 00:16, 10 March 2015
- [[Category:random variables]] Question 1: Probability and Random Processes5 KB (729 words) - 00:51, 10 March 2015
- [[Category:random variables]] Question 1: Probability and Random Processes5 KB (735 words) - 01:17, 10 March 2015
- [[Category:random variables]] Question 1: Probability and Random Processes4 KB (609 words) - 01:54, 10 March 2015
- [[Category:random variables]] Question 1: Probability and Random Processes5 KB (726 words) - 10:35, 10 March 2015
- [[Category:random variables]] Question 1: Probability and Random Processes4 KB (632 words) - 11:05, 10 March 2015
- [[Category:random variables]] Question 1: Probability and Random Processes4 KB (643 words) - 11:16, 10 March 2015
