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A discrete memoryless channel (DMC) can be specified using two random variables , with alphabet ,, and a channel law as a conditional probability distribution (|). The channel capacity , defined as C := sup p ∼ X I ( X ; Y ) {\displaystyle C:=\sup _{p\sim X}I(X;Y)} , indicates the maximum efficiency that a channel can communicate, in the unit ...
GPkit is a Python package for cleanly defining and manipulating geometric programming models. There are a number of example GP models written with this package here . GGPLAB is a MATLAB toolbox for specifying and solving geometric programs (GPs) and generalized geometric programs (GGPs).
Generally, the minimum number of parameters required to describe a model or geometric object is equal to its dimension, and the scope of the parameters—within their allowed ranges—is the parameter space. Though a good set of parameters permits identification of every point in the object space, it may be that, for a given parametrization ...
This can only occur in a smooth channel that does not experience any changes in flow, channel geometry, roughness or channel slope. During uniform flow, the flow depth is known as normal depth (yn). This depth is analogous to the terminal velocity of an object in free fall, where gravity and frictional forces are in balance (Moglen, 2013). [ 3 ]
A binomial distribution with parameters n = 1 and p is a Bernoulli distribution with parameter p. A negative binomial distribution with parameters n = 1 and p is a geometric distribution with parameter p. A gamma distribution with shape parameter α = 1 and rate parameter β is an exponential distribution with rate parameter β.
In fractal geometry, the Higuchi dimension (or Higuchi fractal dimension (HFD)) is an approximate value for the box-counting dimension of the graph of a real-valued function or time series. This value is obtained via an algorithmic approximation so one also talks about the Higuchi method .
Alternatively, the Nakagami distribution (;,) can be generated from the chi distribution with parameter set to and then following it by a scaling transformation of random variables. That is, a Nakagami random variable X {\displaystyle X} is generated by a simple scaling transformation on a chi-distributed random variable Y ∼ χ ( 2 m ...
Golomb coding is a lossless data compression method using a family of data compression codes invented by Solomon W. Golomb in the 1960s. Alphabets following a geometric distribution will have a Golomb code as an optimal prefix code, [1] making Golomb coding highly suitable for situations in which the occurrence of small values in the input stream is significantly more likely than large values.