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Discrete Random Variables
Random variables are nothing but some mathematical functions used for some experiments, and these experiments can be both discrete and continuous. A...
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Continuous Random Variables
In the previous chapters, we focused on the discrete experiments and for the discrete experiments we defined discrete sample spaces, events, and...
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Random Variables
Random variables associate real values with the outcome of a random experiment. This chapter provides a mathematical definition of a random variable...
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Discrete Random Variables
In many applications, the random variableRandom variable \( X \)...
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Functions of Random Variables
For the simple events of a sample space, we can define more than one random variable function; in fact, we can define infinitely many random variable...
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More Than One Random Variables
In this chapter, we consider joint statistical parameters of more than a single random variable. Starting from the joint distribution of two random...
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Dynamical reliability of the stochastic power systems with discrete random variability
In this paper a novel method is presented to analyze the dynamical reliability of the stochastic power systems with discrete random variability. It...
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Random Signals
Random signals arise in all fields of science and engineering. Measurements of all physical variables are never perfect, and the imperfections can be...
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Probability, Random Variables and Random Processes
This chapter contains an introduction to probability, followed by the concept of a random variable. The probability density function (PDF) and...
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Random Variables and Stochastic Processes
Randomness enters into communications problems through the classes of sources, such as speech, images, and music, that we wish to send from one...
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J-type random 2,3 satisfiability: a higher-order logical rule in discrete hopfield neural network
The Discrete Hopfield Neural Network has been widely used for solving combinatorial optimization problems. DHNN is a simple structure with no hidden...
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Continuous Random Variables
The basic theory of the probability has been discussed in Chap. 1 . That knowledge based on the set...
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Analysis of Composite Laminates Strength with Random Deviation Variables
Due to the large dispersion of composite materials, in order to obtain statistical value of the strength of composite laminates, the current method...
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Two parameter generalized entropy of uncertain random variables and its application
Generalized entropy is a flexible risk measure to characterize indeterminacy of uncertain random variables. As important roles of risk measures in...
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Minimum Mean-Square Error Estimation
When dealing with random signals, least-squares estimation must be reformulated to accommodate the randomness of the signal. As usual, we deal with...
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An Improved Discrete Algebraic Reconstruction Technique for Limited-View Based on Gray Mean Value Guidance
Discrete Algebraic Reconstruction Technique (DART) as a heuristic algorithm is capable of computing better results even using fewer numbers of...
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Geometric mean optimizer for achieving efficiency in truss structural design
The objective of this study is to utilize the geometric mean optimizer (GMO) for mass optimization of structural trusses. By harnessing the GMO’s...
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Statistical Analysis of Random Variables
Some reference points are needed to analyze and to make judgments about a given information. For instance, let a boy be...
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Tsallis entropy of uncertain random variables and its application
Tsallis entropy is a flexible extension of Shanon (logarithm) entropy. Since entropy measures indeterminacy of an uncertain random variable, this...
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Infiltration and permeability of porous ceramics simulated by random networks
A network computational model for a 3D ceramic structure is developed. The model is applied to study the impact of geometric and material parameters...
