neural networks seminar or presentation presentation
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29-05-2010, 03:40 PM



.ppt   NEURAL_NETWORK.ppt (Size: 347 KB / Downloads: 130)

Presented By:
AARTI SHARMA
SHREYANS KOTHARI
III BE V SEM


NEURAL NETWORK

BRAIN KE BARABAR


WHAT IS NEURAL NETWORK?

A HIGHLY INTERCONNECTED NETWORK OF INFORMATION PROCESSING ELEMETS THAT MIMICS THE HUMAN BRAIN IN CONNECTIVITY & FUNCTIONALITY


WHERE CAN NEURAL NETWORK SYSTEMS HELP?

WHERE WE CANâ„¢T FORMULATE AN ALGORITHMIC SOLUTION.
WHERE WE CAN GET LOTS OF EXAMPLES.
WHERE WE NEED TO PICK OUT THE STRUCTURE FROM EXISTING DATA.



NEURAL NETWORK ADDRESS PROBLEMS:

PATTERN RECOGNISATION
HANDWRITTEN CHARACTER RECOGNISATION
SPEECH RECOGNISATION
FINANCIAL & ECONOMIC MODELING
NEXT GENERATION COMPUTING MODEL
CLASSIFICATION:



BIOLOGICAL

NEURAL NETWORK
BRAIN IS MOST FAMILIAR EXAMPLE .
APPROX 100 BILLION NERVE CELLS IN IT.
NEURONS CONNECTED TO 10,000 TO 2,00,000 OF OTHER NEURONS.



ARTIFICIAL

NEURAL NETWORK
INPUT LAYER
HIDDEN LAYER
OUTPUT LAYER


BASIC ELEMENTS OF NEURONAL MODEL

A SET OF SYNAPSES OR CONNECTING LINKS.
AN ADDER FOR SUMMING THE INPUTS.
AN ACTIVATION FUNCTION.
TRAINING SETS


NEURAL NETWORK ARE BEING USED IN:

INVESTMENT ANALYSIS.
SIGNATURE ANALYSIS.
PROCESS CONTROL.
MONITERING
PEN PCâ„¢S
SPEECH & VISION RECOGNISATION
WHITE GOODS & TOYS


ADVANTAGES

NON-LINEARITY
INPUT-OUTPUT MAPPING
ADAPTIVITY
EVEDENTIAL RESPONSE
CONTEXTUAL INFORMATION
FAULT TOLERANCE
VLSI IMPLEMENTABILITY
UNIFORMITY OF ANALYSIS & DESIGN
NEUROBIOLOGICAL ANALOGY



CONCLUSION

Today, a solid basis of theory and applications is being formed and the field has begun to flourish. For a growing list of applications, the neural architecture will provide either an alternative or a complement to these other techniques.



REFRENCES

NEURAL NETWORKS
- SIMON HAYKIN
ENCARTA ENCYCLOPEDIA
GOOGLE SEARCH ENGINE



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