Introduction to Adaptive and Neural Networks

What is an Adaptive Network?

• a network of simple, interconnected processors that "learns from" and "adapts to" changing conditions
  
• can be simulated on a general-purpose computer such as a PC or incorporated in high-speed, low-cost, special-purpose electronic "chips"
  

What is a Neural Network?

• The "real" Neural Networks are those biological networks invented by nature to sense, learn from, and interpret the world, e.g., the brain, the visual cortex, and the sensory-motor systems of living beings
  
• An "Artificial Neural Network" is a form of Adaptive Network that is motivated by the architecture of biological networks; often the term Neural Network means "Artificial Neural Network"; also, the distinction between Adaptive and Neural Networks is generally blurred
  

When do you need an Adaptive Network?

• to perform tasks that are difficult for other technical approaches
  
• to perform tasks that require "learning", "judgement" or "intelligence"
  
• to infer or learn from "data-rich", "understanding-poor" situations
  
• to perform tasks that require human attention, but are repetitious or hazardous
  
• to predict and control chaotic dynamical systems

• Some versatile and capable Adaptive and Neural Network tools
  
• Some successful NN Application Examples
  

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