Anurag RANA

Anurag 1. What is Software Testing? Software testing is more than just error detection;   Testing software is operating the software under controlled conditions, to (1) verify that it behaves “as specified”; (2) to detect errors , and (3) to validate that what has been specified is what the user actually wanted. Verification is the checking or testing of items, including software, for conformance and consistency by evaluating the results against pre-specified requirements.  [ V erification: Are we building the system right? ] Error Detection : Testing should intentionally attempt to make things go wrong to determine if things happen when they shouldn’t or things don’t happen when they should. Validation looks at the system correctness – i.e. is the process of checking that what has been specified is what the user actually wanted.  [ Validation: Are we building the right system? ] In other wo...

Anurag That is a valid question. Why Neural Networks? Neural Network is a fascinating technology, 50 years old, but still not fully employed. And the question is why? Why didn't Neural Network progress as fast as many other technologies? Let us first take a look back … The concept of neural networks has been around since the early 1950s, but was mostly dormant until the mid 1980s. One of the first neural networks developed was the perceptron created by a psychologist named Frank Rosenblatt in 1958. The perceptron was a very simple system used to analyze data and visual patterns, which generated a great deal of interest in AI community. Unfortunately, these earlier successes caused people to exaggerate the potential of neural networks, particularly in light of the limitation in the electronics then available. Rosenblatt and other scientists claimed that eventually, with enough complexity and speed, the perceptron would be able to solve almost any problem. In 1969, Marvi...

Anurag                                  INTRODUCTION 1.1 INTRODUCTION Borrowing from biology, researchers are exploring neural networks—a new, non algorithmic approach to information processing. A Neural Network is a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human brain. Neural networks resemble the human brain in the following two ways: Ø     A neural network acquires knowledge through learning. Ø     A neural network's knowledge is stored within inter-neuron connection strengths known as synaptic weights. 1.2 ADVANTAGES OF NEURAL NET...