23-05-2012, 03:20 PM
OFDM AND OFDM CHANNEL ESTIMATION
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Weibull distribution
In probability theory and statistics, the Weibull distribution [1] is a continuous probability distribution. The probability density function of a Weibull random variable x is:
where k > 0 is the shape parameter and λ > 0 is the scale parameter of the distribution. Its complementary cumulative distribution function is a stretched exponential function. The Weibull distribution is related to a number of other probability distributions; in particular, it interpolates between the exponential distribution (k = 1) .
Normal Distribution
In probability theory and statistics, the normal distribution [2] or Gaussian distribution is a continuous probability distribution that often gives a good description of data that cluster around the mean. The graph of the associated probability density function is bell-shaped, with a peak at the mean, and is known as the Gaussian function or bell curve. Probablity distribution of Normal distribution of random variable x whose mean is and variance is given by:
Gamma Distribution
In probability theory and statistics, the gamma distribution [3] is a two-parameter family of continuous probability distributions. It has a scale parameter θ and a shape parameter k. The gamma distribution is frequently a probability model for waiting times; for instance, in life testing, the waiting time until death is a random variable that is frequently modeled with a gamma distribution.
Exponential Distribution
In probability theory and statistics, the exponential distributions [4] are a class of continuous probability distributions. They describe the times between events in a Poisson process, i.e. a process in which events occur continuously and independently at a constant average rate.
Rayleigh Distribution
In probability theory and statistics, the Rayleigh distribution [5] is a continuous probability distribution. As an example of how it arises, the wind speed will have a Rayleigh distribution if the components of the two-dimensional wind velocity vector are uncorrelated and normally distributed with equal variance.
[attachment=22899]
Weibull distribution
In probability theory and statistics, the Weibull distribution [1] is a continuous probability distribution. The probability density function of a Weibull random variable x is:
where k > 0 is the shape parameter and λ > 0 is the scale parameter of the distribution. Its complementary cumulative distribution function is a stretched exponential function. The Weibull distribution is related to a number of other probability distributions; in particular, it interpolates between the exponential distribution (k = 1) .
Normal Distribution
In probability theory and statistics, the normal distribution [2] or Gaussian distribution is a continuous probability distribution that often gives a good description of data that cluster around the mean. The graph of the associated probability density function is bell-shaped, with a peak at the mean, and is known as the Gaussian function or bell curve. Probablity distribution of Normal distribution of random variable x whose mean is and variance is given by:
Gamma Distribution
In probability theory and statistics, the gamma distribution [3] is a two-parameter family of continuous probability distributions. It has a scale parameter θ and a shape parameter k. The gamma distribution is frequently a probability model for waiting times; for instance, in life testing, the waiting time until death is a random variable that is frequently modeled with a gamma distribution.
Exponential Distribution
In probability theory and statistics, the exponential distributions [4] are a class of continuous probability distributions. They describe the times between events in a Poisson process, i.e. a process in which events occur continuously and independently at a constant average rate.
Rayleigh Distribution
In probability theory and statistics, the Rayleigh distribution [5] is a continuous probability distribution. As an example of how it arises, the wind speed will have a Rayleigh distribution if the components of the two-dimensional wind velocity vector are uncorrelated and normally distributed with equal variance.