Question

TYPED PLEASE!!!!!

Briefly discuss the application of Poisson processes to a telecommunication engineer. [6 marks]
Distinguish between a Homogeneous Poisson Process and a Non-Homogeneous Poisson Process [7 marks]
Briefly discuss the following terms.
i. Machine learning. [3 marks]
ii. Neural networks, genetic programming. [3 marks]
iii. Genetic programming.

Answer 1

Poisson process is the distribution followed by arrivals into a system - the arrival times here are often considered to follow a Poisson process, with the mean time between arrivals as the parameter of the Poisson distribution modeling this process.

In telecommunications, we often model the telephone calls arriving in a system as a Poisson process. The incoming call rate is random and it it often useful to model the distribution of call arrivals (incoming call times) as a Poisson process.

i) Machine Learning: Machine learning is a set of technique used by machines to learn and improve from examples and experience, without being explicitly programmed. It consists of developing programs that automatically develop with experience.

ii) Neural Networks: Neural Networks is a set of algorithms that aims to recognize underlying relationships in a set of data through a process that mimics the way human brain operates. They are designed to adapt to changing inputs and improve with experience. They're a type of deep learning technique, and are used in time series forecasting, algorithmic trading, pricing derivative instruments in finance, etc

iii) Genetic programming: The technique of improving programs starting from relatively less smarter programs, by applying a operations similar to natural genetic processes. It automatically breeds computer programs using the biological principal of natural selection, crossover, mutation, reproduction, etc.