What is Fuzzy Logic?
Fuzzy logic is a form of
many-valued logic in which
the truth values of variables
may be any real number
between 0 and 1. By contrast,
in Boolean logic, the truth
values of variables may only
be the integer values 0 or 1.
EXAMPLE
Temperature measurement for
AC
RED ARROW(points to zero)-
Not Hot
ORANGE ARROW(points to 0.2)-
Slightly Warm
BLUE ARROW(points to 0.8)-
Fairy Cold
Fuzzy Logic System Architecture
Defuzzification
Module
● It transforms the fuzzy set
obtained by the inference engine
into a crisp value.
Knowledge Base
● It stores IF-THEN rules provided
by experts.
Fuzzification
Module
● It transforms the system inputs,
which are crisp numbers, into
fuzzy sets.
Inference Engine
● It simulates the human reasoning
process by making fuzzy inference
on the inputs and IF-THEN rules.
ABS(ANTI-LOCK BRAKING SYSTEM)
ABS is the safety system which prevents the wheels
on a motor vehicle from locking up(or skidding)
while braking keeping the vehicle speed and the
wheel speed at a same level.
ABS which is a nonlinear system may not work on
simple classical control methods.
Fuzzy ABS require more complex control constructs
than the simple "if-then" rules.But in fuzzy control it
is possible to build a control with intermediate fuzzy
variables.
PROS
● Mathematical concepts
within fuzzy reasoning are
very simple.
● Fuzzy logic Systems can
take imprecise, distorted,
noisy input information.
● Fuzzy logic is a solution to
complex problems in all
fields of life, including
medicine(like human).
CONS
● There is no systematic
approach to fuzzy system
designing.
● They are understandable
only when simple.
● They are suitable for the
problems which do not
need high accuracy.
What is Deep Learning ?
Why Deep Learning ?
Deep Learning skips the manual steps of extracting features,you can directly fees images
to the deep learning algorithms,which then predicts the object.
How Deep Learning works ?
NEURAL NETWORKS
Why we need Artificial Neuron ?
Single Layered Neural Network- “Perceptron”
Perceptron Learning Algorithm
Implementation of Neural Networks In GATES
Overview of Artificial Neural Networks and its
Applications
One of the largest U.S bank JP Morgan Chase used
Watson’s AI to analyze credit card transactions :
Image credit - Facebook AI Research
Facebook has developed an AI that can react naturally to
Human Expressions
AI can build an AI !!
Thank You
Sharmi Das Saket Raj
sharmiabc@gmail.com saketraj46@gmail.com
Saurav Prasad
sauravprasad.1996@gmail.com

Neural networks and fuzzy logic

  • 2.
    What is FuzzyLogic? Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1. By contrast, in Boolean logic, the truth values of variables may only be the integer values 0 or 1.
  • 3.
    EXAMPLE Temperature measurement for AC REDARROW(points to zero)- Not Hot ORANGE ARROW(points to 0.2)- Slightly Warm BLUE ARROW(points to 0.8)- Fairy Cold
  • 4.
    Fuzzy Logic SystemArchitecture Defuzzification Module ● It transforms the fuzzy set obtained by the inference engine into a crisp value. Knowledge Base ● It stores IF-THEN rules provided by experts. Fuzzification Module ● It transforms the system inputs, which are crisp numbers, into fuzzy sets. Inference Engine ● It simulates the human reasoning process by making fuzzy inference on the inputs and IF-THEN rules.
  • 5.
    ABS(ANTI-LOCK BRAKING SYSTEM) ABSis the safety system which prevents the wheels on a motor vehicle from locking up(or skidding) while braking keeping the vehicle speed and the wheel speed at a same level. ABS which is a nonlinear system may not work on simple classical control methods. Fuzzy ABS require more complex control constructs than the simple "if-then" rules.But in fuzzy control it is possible to build a control with intermediate fuzzy variables.
  • 6.
    PROS ● Mathematical concepts withinfuzzy reasoning are very simple. ● Fuzzy logic Systems can take imprecise, distorted, noisy input information. ● Fuzzy logic is a solution to complex problems in all fields of life, including medicine(like human). CONS ● There is no systematic approach to fuzzy system designing. ● They are understandable only when simple. ● They are suitable for the problems which do not need high accuracy.
  • 8.
    What is DeepLearning ?
  • 10.
    Why Deep Learning? Deep Learning skips the manual steps of extracting features,you can directly fees images to the deep learning algorithms,which then predicts the object.
  • 11.
  • 12.
  • 13.
    Why we needArtificial Neuron ?
  • 14.
    Single Layered NeuralNetwork- “Perceptron”
  • 15.
  • 16.
    Implementation of NeuralNetworks In GATES
  • 17.
    Overview of ArtificialNeural Networks and its Applications
  • 21.
    One of thelargest U.S bank JP Morgan Chase used Watson’s AI to analyze credit card transactions :
  • 22.
    Image credit -Facebook AI Research Facebook has developed an AI that can react naturally to Human Expressions
  • 23.
    AI can buildan AI !!
  • 24.