Neural Networks

Neural Networks have a remarkable ability to derive meaning from complicated or imprecise data. We like to think of a Neural Network as a “baby computer brain” that becomes more intelligent as it is fed more “information.”

Technically, a trained neural network can be thought of as an "expert" in the category of information it has been given to analyze. This expert can then be used to provide projections given new situations of interest and answer "what if" questions.

Techniques we have experience with include:      

  1. Adaptive learning: An ability to learn how to do tasks based on the data given for training or initial experience.
  2. Self-Organization: An artificial neural network can create its own organization or representation of the information it receives during learning time.
  3. Real Time Operation: ANN computations may be carried out in parallel and special hardware devices are being designed and manufactured which take advantage of this capability.
  4. Fault Tolerance via Redundant Information Coding: Partial destruction of a network leads to the corresponding degradation of performance. However, some network capabilities may be retained even with major network damage.
  5. Genetic Algorithms: Search heuristics that mimic the process of natural evolution. These heuristics are routinely used to generate useful solutions to optimization and search problems.

Access Softek has incorporated neural networks into security features, targeted marketing strategies, data mining, and image analysis. Our algorithms are at the cutting-edge of AI (Artificial Intelligence).