Interval Type-2 Fuzzy System and its Applications

Abstract: This talk will be delivered in two parts while the first part is a brief introduction of fuzzy logic systems from the control point of view while the second part is about the fuzzy-logic related applications. In the first part, the fuzzy logic system will be introduced and its fundamentals, working principle, and rationale will be explained in detail with the support of block diagrams and examples. The role of type-1, interval type-2, and general type-2 fuzzy sets will be discussed, and their pros and cons will be highlighted. In the second part, the applications using fuzzy-model-free and fuzzy-model-based techniques will be covered which include the control of the mobile robot, decision making and obstacle avoidance for robot soccer, drug administration of anesthesia, classification of epilepsy phases, balancing of an inverted pendulum, torque control of bolt-tightening applications and tracking control of continuum manipulator. The contributions of the presenter made to the filed, which initiated two research sub-fields underpinning the imperfect premise matching concept, membership-function-dependent analysis, and interval type-2 fuzzy-model-based control systems, will be summarised.

Slides are available here: Interval Type-2 Fuzzy System and its Applications

Introduction to Fuzzy Logic Systems

Abstract: This video is about the introduction of Fuzzy Logic Systems/Fuzzy Inference Systems. The basic concept of fuzzy sets and the working principle of a Fuzzy Logic System/Fuzzy Inference System will be described. A fuzzy controller implemented by a Fuzzy Logic System/Fuzzy Inference System is employed for position control of a two-wheeled mobile robot. It also shows that fuzzy logic can be applied to obstacle avoidance and robot soccer applications.

Support Vector Machines

This is a series of videos about Support Vector Machines (SVMs), which will walk through the introduction, the working principle and theory covering a linearly separable case, non-separable case, nonlinear SVM and multiple-class SVMs.

Part 1: Introduction

Part 2a: Linearly Separable Case

Part 2b: Linearly Separable Case (cont'd)

Part 3: Non-separable Case

Part 4: Nonlinear SVMs

Part 5:  Multi-class SVMs

Multilayer Neural Networks

This is a series of video about multi-layer neural networks, which will walk through the introduction, the architecture of feedforward fully-connected neural network and its working principle, the working principle of backpropagation learning algorithm, and the working principle and learning issues of radial-basis-function (RBF) neural network.

Part 1: Introduction

Part 2a: Feedforward Neural Network

Part 2b: Feedforward Neural Network - An Example

Part 3a: Backpropagation I

Part 3b: Backpropagation II

Part 4: Radial Basis Function (RBF) Neural Network and Learning Issues

Generative Adversarial Networks (GANs)

This is a series of video about Generative Adversarial Networks (GANs), which will introduce the basic GAN structure,  working principle and training algorithm.

Part 1

Part 2

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