Documentation update authored by Shuvra S. Bhattacharyya's avatar Shuvra S. Bhattacharyya
The NEural DEcoding COnfiguration (NEDECO) Package provides an optimization
framework for automated and holistic parameter optimization of neural decoding
systems. The framework considers both algorithmic and dataflow parameters while
jointly taking into account both the neural decoding accuracy and execution
time of the optimized solutions. The framework applies a population-based
search strategy to optimize the relevant algorithmic and dataflow parameters of
the given neural decoding system. The framework is general in that a variety of
search strategies can be plugged-in; it is not specific to a single type of
search method. Presently, two different search strategies are integrated into
NEDECO --- Particle Swarm Optimization (PSO), and and Genetic Algorithms (GAs).
The objective of the NEDECO package is to help experimental
neuroscientists and neural decoding system designers to arrive at
strategically-optimized configurations of neural decoding implementations.