I am working on pseudo random number generation topic. To be precise, Inverse Transform Sampling method , i.e., a method for generating sample numbers at random from any probability distribution given its cumulative distribution function.
The problem that the inverse transform sampling method solves is as follows:
- Let X be a random variable whose distribution can be described by the cumulative distributive function Fx.
- I want to generate values of X which are distributed according to this distribution.
The exact reference of what I would like to implement on FPGA is : https://en.wikipedia.org/wiki/Inverse_transform_sa...
- What would be the mathematical challenges? I mean challenges in context of natural log and then data types like integer, fixed and floating points.
- What should be the right approach? I mean the starting point.
I am looking for some example codes (if any) and helping literature that would help me to understand the granularity of implementation on FPGA.
Looking forward to suggestions. Thanks a lot !
You can easily use IP so called random number generator. It allows you to define the random sequence seed manually. The uniformly distributed integer number generator is a random sequence of 32 bit data, which can be interpreted as signed or unsigned integer. Refer to link below for details