Title :
Generation and validation of Gaussian noise using random sequence
Author :
Pardhu, Thottempudi ; Nelakuditi, Usha Rani ; Pampana, Suresh
Author_Institution :
Vignan Univ., Vadlamudi, India
Abstract :
In general many real time problems are represented with random variables. But a random variable is characterized by a Probability Density Function(PDF). As per the Central Limit Theorem any stochastic process handled with many random variables can be converged as a normal distribution. Hence normal distribution plays a key role in modeling real time problems contains many random variables. This paper dealt with the generation of Gaussian PDF using uniform random sequence. The generated PDF is validated in LABVIEW.
Keywords :
Gaussian noise; normal distribution; random number generation; random sequences; Gaussian PDF; Gaussian noise generation; Gaussian noise validation; LABVIEW; central limit theorem; normal distribution; probability density function; random variable; stochastic process; uniform random sequence; Algorithm design and analysis; Field programmable gate arrays; Gaussian noise; MATLAB; Real-time systems; Very large scale integration; Gaussian noise; LABVIEW; PDF; Random Sequence;
Conference_Titel :
Electronics and Communication Systems (ICECS), 2014 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-2321-2
DOI :
10.1109/ECS.2014.6892661
