Definition
Non linear unites called “ Neurons”
inter connected via weighted branches (synaptic ) in layers each layer has it’s
own computations and passes the results to the next layer dealing with info
in parallel and simultaneously and
posses the ability to learning and adaptation .
Types of ANNs “Artificial Neural Network”
A- Static :
1-
Don’t contain any memory elements.
2-
I/O relation is nonlinear function.
B- dynamic :
1- Contain memory
elements.
2- I/O relation differential
equation.
Neural Network Applications
Aerospace:
High performance aircraft
autopilot, flight path simulation, aircraft control
systems, autopilot
enhancements, aircraft component simulation, aircraft
component fault
detection.
Automotive:
Automobile automatic
guidance system, warranty activity analysis.
Banking:
Check and other document
reading, credit application evaluation.
Credit Card Activity Checking:
Neural networks are used
to spot unusual credit card activity that might
possibly be associated
with loss of a credit card.
Defense:
Weapon steering, target
tracking, object discrimination, facial recognition,
new kinds of sensors,
sonar, radar and image signal processing including
data compression, feature
extraction and noise suppression, signal/image
identification.
Electronics:
Code sequence prediction,
integrated circuit chip layout, process control,
chip failure analysis,
machine vision, voice synthesis and nonlinear modeling.
Entertainment:
Animation, special
effects, market forecasting.
Financial:
Real estate appraisal,
loan advisor, mortgage screening, corporate bond
rating, credit-line use
analysis, portfolio trading program, corporate
financial
analysis, currency price prediction.
Industrial:
Neural networks are being
trained to predict the output gasses of furnaces
and other industrial
processes. They then replace complex and costly
equipment used for this
purpose in the past.
Insurance:
Policy application
evaluation, product optimization.
Manufacturing:
Manufacturing process
control, product design and analysis, process and
machine diagnosis,
real-time particle identification, visual quality
inspection systems, beer
testing, welding quality analysis, paper quality
prediction, computer-chip
quality analysis, analysis of grinding operations,
chemical product design
analysis, machine maintenance analysis, project
bidding, planning and
management, dynamic modeling of chemical process
system.
Medical:
Cancer cell analysis, EEG
and ECG analysis, prosthesis design,
optimization of
transplant times, hospital expense reduction, hospital
quality improvement,
emergency-room test advisement.
Oil and Gas:
Exploration.
Robotics:
Trajectory control,
forklift robot, manipulator controllers, vision systems.
Speech:
Speech recognition,
speech compression, vowel classification, text-to-speech
Synthesis.
Securities:
Market analysis,
automatic bond rating, stock trading advisory systems.
Telecommunications:
Image and data
compression, automated information services, real-time
translation of spoken
language, customer payment processing systems.
Transportation:
Truck brake diagnosis
systems, vehicle scheduling, routing systems.
Properties of Neural controllers
a- nonlinear by nature which is suited to control nonlinear Plants.
b-
Parallel processing that leads to higher reliability and fault tolerance,
speed .
c-
Learning and adaptation that operates with subjects they weren’t trained.
d-
Multivariable which process multi i/ps
generate M o/ps
e-
Relative immune to noise.
g- Easy
implemented.
Hi. I’m Designer of Engineering Topics Blog. I’m Electrical Engineer And Blogger Specializing In Electrical Engineering Topics. I’m Creative.I’m Working Now As Maintenance Head Section In An Industrial Company.
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