ARTIFICIAL INTELLIGENCE (AI):
Neural Networks and Fuzzy Logic Fundamentals
Course Description
The complexity and dynamics of real-world problems, such as prediction, decision making for robots, control systems, large bioinformatics data processing, adaptive speech recognition and language acquisition, visual monitoring systems and multi-modal information processing, and intelligent agent based systems and adaptive agents on the web, require sophisticated methods and tools for building online, knowledge based intelligent systems. Such systems should be able to do the following.
- Learn adaptively
- Dynamically create new modules
- Memorize information
- Interact continuously
- Deal with knowledge
The Neural networks and Fuzzy logic systems have been developed to meet the criteria above.
Course Objective
This 2 Day course will first discusses the fundamental principle of neural network and fuzzy logic, and then gives insight to tools available in MATLAB and SIMULINK to solve the complex and dynamic real-world problems. Numerous examples will be given to support the discussed theory.
Pre-requisites:
Candidtate must have experience with
basic computer operations and must be
knowledgeable in basic Matlab and
Simulink usage. Preferably you have
attended our "Learner's Guide to MATLAB® " and "Learner’s Guide to SIMULINK® "
Course Outline:
Day 1
- Neural Network concepts
- Introduction
- Simple neuron model
- MATLAB representation of neural network
- Type of Learning Methods
- Back propagation
- Least Square
- Steepest descent
- Type of Neural Network
- Perceptrons
- Linear networks
- Multi layer perceptrons
- Self-organizing maps
- Case Study
Day 2
- Fuzzy Logic Concepts
- Introduction
- Fuzzy Sets
- Membership functions
- Logical operations
- If-Then rules
- Fuzzy inferences systems (FIS)
- Introduction
- Building FIS with Fuzzy GUI
- Working from the command line
- Application examples
- Adaptive Neural-Fuzzy Inference Systems (ANFIS)
- Sugeno-type fuzzy inferenc
- The ANFIS editor GUI
- Working from the command line
- Application examples
- Case Studies
Who Should Attend
Engineers, researchers, scientists, postgraduate students, R&D staffs, and those who like to understand the principle of neural networks and fuzzy logic with their applications with MATLAB. .
Course Benefits
Upon the completion of the course, the participants should be able to use the toolboxes for artificial intelligent to not only solve complex real-world problems, but also provide solutions for problems in research and development or education.
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