Search results for "Discrete random variable" - Rhea

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• ECE PhD QE CNSIP Jan 2001 Problem1
  [[Category:random variables]] Question 1: Probability and Random Processes
  4 KB (616 words) - 10:19, 13 September 2013
• ECE PhD QE CNSIP Jan 2006 Problem1
  [[Category:random variables]] Question 1: Probability and Random Processes
  4 KB (572 words) - 10:24, 10 March 2015
• 2013 Spring ECE 302 Boutin
  Probability, Statistics, and Random Processes for Electrical Engineering, 3rd Edition, by Alberto Leon-Garcia, *Discrete Random Variables
  10 KB (1,422 words) - 20:14, 30 April 2013
• LectureScheduleECE302Spring13 Boutin
  ==Part 2: Discrete Random Variables (To be tested in the second intra-semestrial exam)== *2.2 Functions of a discrete random variable
  4 KB (498 words) - 10:18, 17 April 2013
• Lecture11 blog ECE302S13 Boutin
  ...short illustration of a research-level image processing problem for which discrete distributions are useful.
  2 KB (307 words) - 10:26, 4 February 2013
• Lecture12 blog ECE302S13 Boutin
  ...xamples. A formula for computing the expectation of a function of a random variable was also given. Along the way, we encountered the geometric series. Those w
  3 KB (341 words) - 09:59, 5 February 2013
• Lecture15 blog ECE302S13 Boutin
  ...iz in which you were asked to compute the Expectation of a discrete random variable. Twitter disrupted the lecture slightly, but I trust all of us will make a
  2 KB (335 words) - 13:00, 18 February 2013
• Lecture16 blog ECE302S13 Boutin
  ...dom variable does not change the variance, and that multiplying the random variable by a constant "a" has the effect of multiplying the variance by <math>a^2</
  2 KB (336 words) - 12:59, 18 February 2013
• Lecture17 blog ECE302S13 Boutin
  ...III of the material with a definition of the concept of "continuous random variable" along with two examples.
  2 KB (321 words) - 11:12, 15 February 2013
• Practice Question probability normalization ECE302S13Boutin
  [[Category:discrete random variable]] ...Problem]]: normalizing the probability mass function of a discrete random variable=
  2 KB (355 words) - 13:50, 13 February 2013
• HW4 ECE302 S13 Boutin
  *On question 16 and 27, how do you deal with a infinite discrete random variable x? How do you calculate the probabilities with only known expected value? ...known, note that it is generally impossible to derive the pmf of a random variable only from its expected value. However, there is something remarkable about
  2 KB (302 words) - 10:52, 19 February 2013
• Lecture18 blog ECE302S13 Boutin
  ...at an example of continuous random variable, namely the exponential random variable.
  2 KB (329 words) - 08:16, 20 February 2013
• Lecture19 blog ECE302S13 Boutin
  In Lecture 19, we continued our discussion of continuous random variables. ...nvent a problem about the expectation and/or variable of a discrete random variable]]
  2 KB (252 words) - 08:20, 20 February 2013
• Lecture20 blog ECE302S13 Boutin
  ...us and discrete) and we began discussing normally distributed (continuous) random variables. ...02S13Boutin|Normalizing the probability mass function of a Gaussian random variable]]
  2 KB (304 words) - 07:43, 23 February 2013
• Bonus point 3 ECE302 Spring2012 Boutin
  ...a problem related to the expectation and/or variance of a discrete random variable and solve it. Then post your problem and solution on a Rhea page, and post [[Category:discrete random variable]]
  3 KB (467 words) - 18:17, 27 February 2013
• ThirdBonusDude91
  ...gory:probability]] [[Category:problem solving]] [[Category:discrete random variable]] [[Category:expectation]] [[Category:variance]]
  4 KB (757 words) - 06:59, 22 February 2013
• ECE302 EC2 Woo
  ...gory:probability]] [[Category:problem solving]] [[Category:discrete random variable]][[Category:expectation]] [[Category:variance]] ...vels from -2 V to 2 V with 1V difference. After the counter has sent out a random signal, each noise level has probability of {1/10,2/10,4/10,2/10,1/10}. The
  2 KB (299 words) - 18:13, 27 February 2013
• Lecture27 blog ECE302S13 Boutin
  ...iable. We also discussed the problem of recovering the pdf/pmf of a random variable from its moment generating function. ...CE302S13Boutin|Obtain the characteristic function of an exponential random variable]]
  2 KB (336 words) - 09:39, 18 March 2013
• Temporary file ECE302S12Boutin
  ...and let Y be the arrival time of the professor. Assume that the 2D random variable (X,Y) is uniformly distributed in the square [2 , 3]x[2,3]. '''2.''' Let (X,Y) be a 2D random variable that is uniformly distributed in the rectangle [1,3]x[5,10].
  3 KB (559 words) - 07:02, 22 March 2013
• Practice Question what is stationary increment property sum process ECE302S13
  [[Category:random process]] ...ariable with the same distribution as the random variable contained in the random process at the time found by differencing the two distinct times mentioned
  9 KB (1,507 words) - 16:23, 23 April 2013
• Quiz4 expectation discrete RV ECE302 S13 Boutin
  Topic: Expectation of discrete random variable *Let X be a discrete random variable with probability mass function
  782 B (106 words) - 14:19, 25 April 2013
• ECE600 F13 rv definition mhossain
  [[ECE600_F13_rv_distribution_mhossain|Next Topic: Random Variables: Distributions]] [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']]
  7 KB (1,194 words) - 12:11, 21 May 2014
• ECE600 F13 rv distribution mhossain
  [[ECE600_F13_rv_definition_mhossain|Previous Topic: Random Variables: Definitions]]<br/> [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']]
  15 KB (2,637 words) - 12:11, 21 May 2014
• ECE600 F13 rv conditional distribution mhossain
  [[ECE600_F13_rv_distribution_mhossain|Previous Topic: Random Variables: Distributions]]<br/> ...rv_Functions_of_random_variable_mhossain|Next Topic: Functions of a Random Variable]]
  6 KB (1,109 words) - 12:11, 21 May 2014
• ECE600 F13 rv Functions of random variable mhossain
  [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] <font size= 3> Topic 8: Functions of Random Variables</font size>
  9 KB (1,723 words) - 12:11, 21 May 2014
• ECE600 F13 Expectation mhossain
  ...unctions_of_random_variable_mhossain|Previous Topic: Functions of a Random Variable]]<br/> [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']]
  8 KB (1,474 words) - 12:12, 21 May 2014
• ECE600 F13 Characteristic Functions mhossain
  [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] ...pdf f<math>_X</math> of a random variable X is a function of a real valued variable x. It is sometimes useful to work with a "frequency domain" representation
  5 KB (804 words) - 12:12, 21 May 2014
• ECE600 F13 Joint Distributions mhossain
  [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] <font size= 3> Topic 11: Two Random Variables: Joint Distribution</font size>
  8 KB (1,524 words) - 12:12, 21 May 2014
• ECE600 F13 Joint Expectation mhossain
  [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] Given random variables X and Y, let Z = g(X,Y) for some g:'''R'''<math>_2</math>→R. Th
  7 KB (1,307 words) - 12:12, 21 May 2014
• ECE600 F13 Conditional Distributions for Two Random Variables mhossain
  [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] <font size= 3> Topic 15: Conditional Distributions for Two Random Variables</font size>
  6 KB (1,139 words) - 12:12, 21 May 2014
• ECE600 F13 Stochastic Convergence mhossain
  [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] We will now consider infinite sequences of random variables. We will discuss what it means for such a sequence to converge. T
  15 KB (2,578 words) - 12:13, 21 May 2014
• ECE600 F13 Stochastic Processes mhossain
  [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] ...s, but we will now formalize the concept of random process, including both discrete-time and continuous time.
  10 KB (1,690 words) - 12:13, 21 May 2014
• ECE-QE CS1-2012
  [[Category:random variables]] Question 1: Probability and Random Processes
  3 KB (449 words) - 21:36, 5 August 2018
• ECE-QE CS1-2012 solusion-1
  <font size="4">Question 1: Probability and Random Processes </font> ...our proof, keep in mind that may be either a discrete or continuous random variable.
  6 KB (995 words) - 09:21, 15 August 2014
• Walther375Spring2014 Markov chains: what and how?
  ...cess. 
 A stochastic process { X(t), t∈T } is an ordered collection of random variables, T where T is the index set and if t is a time in the set, X(t) i ...h models that use X1,…,Xn as independently identically distributed (iid) random variables. However, note that states do not necessarily have to be independ
  19 KB (3,004 words) - 09:39, 23 April 2014
• Bayes Parameter Estimation
  ...ven value of θ is denoted by p(x|θ ). It should be noted that the random variable X and the parameter θ can be vector-valued. Now we obtain a set of indepen ...s parameter estimation, the parameter θ is viewed as a random variable or random vector following the distribution p(θ ). Then the probability density func
  15 KB (2,273 words) - 10:51, 22 January 2015
• Maximum Likelihood Estimation Analysis for various Probability Distributions
  ...tinuous random variables and probability mass function in case of discrete random variables and 'θ' is the parameter being estimated. ...variables) or the probability of the probability mass (in case of discrete random variables)'''
  12 KB (1,986 words) - 10:49, 22 January 2015
• ECE PhD QE CNSIP 2003 Problem1.4
  [[Category:random variables]] Question 1: Probability and Random Processes
  3 KB (538 words) - 00:54, 10 March 2015
• ECE PhD QE CNSIP Jan 2006 Problem1.2
  [[Category:random variables]] Question 1: Probability and Random Processes
  3 KB (454 words) - 10:25, 10 March 2015