• Proceedings of the KIEE Conference
• /
• 2000.11d
• /
• pp.803-805
• /
• 2000

In this paper, we propose fuzzy-neural Networks(FNN) which is useful for identification algorithms. The proposed FNN model consists of two steps: the first step, which determines premise and consequent parameters approximately using FCM_RI method, the second step, which adjusts the premise and consequent parameters more precisely by gradient descent algorithm. The FCM_RI algorithm consists FCM clustering algorithm and Recursive least squared(RLS) method, this divides the input space more efficiently than convention methods by taking into consideration correlations between components of sample data. To evaluate the performance of the proposed FNN model, we use the time series data for gas furnace.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1-4
• /
• 1996

It is difficult that a non-translational motion in a block is estimated by the block matching algorithm (BMA). In this paper, a nodal-displacement-based deformation model is used for this reason. This model assumes that a selected number of control nodes move freely in a block and that displacement of any interior point can be interpolated from nodal displacements. As a special case with a single node this model is equivalent to a translational model. And this model can represent more complex deformation using more nodes. We used an iterative gradient based search algorithm to estimate nodal displacement. Each iteration involves the solution of a simple linear equation. This method is called the deformable block matching algorithm (DBMA).

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.8
• /
• pp.914-922
• /
• 1999

A study on the improvement of tracking performance of a 3 DOF planar parallel manipulator is performed. A class of adaptive tracking control sheme is designed using self tuning adaptive fuzzy logic control theory. This control sheme is composed of three classical PD controller and a multi learning type self tuning adaptive fuzzy logic controller set. PD controller is tuned roughly by manual setting a priori and fuzzy logic controller is tuned precisely by the gradient descent method for a global solution during run-time, so the proposed control scheme is tuned more rapidly and precisely than the single learning type self tuning adaptive fuzzy logic control sheme for a local solution. The control performance of the proposed algorithm is verified through experiments.

• Journal of the Korea Computer Graphics Society
• /
• v.23 no.3
• /
• pp.47-54
• /
• 2017

In this paper, we propose an improved curvature-based GPU (Graphics Processing Unit) isosurface ray-casting technique. Our method adopts the fast evaluation method proposed by Sigg et al. [1] to find the isosurface, but replaces the computation of the gradient and Hessian with the de Boor algorithm. In this way, we can reduce the number of additional texture fetches from 84 to 27 thus improving the performance by up to ${\approx}30%$, depending on the platforms.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.933-935
• /
• 1999

In this paper, we present model predictive control scheme based on neural network to control discrete-time chaotic systems. We use a feedforward neural network as nonlinear prediction model. The training algorithm used is an adaptive backpropagation algorithm that tunes the connection weights. And control signal is obtained by using gradient descent (GD), some kind of LMS method. We identify that the system identification results through model prediction control have a great effect on control performance. Finally, simulation results show that the proposed control algorithm performs much better than the conventional controller.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.659-661
• /
• 1999

In this paper, we proposed a simple neural network-based parameter tuning algorithm, which could find the gradients of a certain performance index in the PID parameter spaces. In this process, we had to know the dynamics between input and output of the plant, and we used the Back Propagation Neural network to identify them. To make the parameter updating fast and smooth, we constructed the performance index as the sum of past N-squared plant errors, and applied a batch mode algorithm to update parameters. We performed several experiments with a DC Motor to show the validity of the proposed algorithm.

• Transactions on Control, Automation and Systems Engineering
• /
• v.1 no.1
• /
• pp.69-74
• /
• 1999

Adaptive algorithms based on gradient adaptation have been extensively investigated and successfully joined with active noise/vibration control applications. The Filtered-X LMS algorithm became one of the basic feedforward algorithms in such applications, but is not fully understood yet. Effects of cancellation path model on the Filtered-X LMS algorithm have investigated and some useful properties related to stability were discovered. Most of the results stated that the error in the cancellation path model is undesirable to the Filtered X LMS. However, we started convergence analysis of Filtered-X LMS based on the assumption that erroneous model does not always degrade its performance. In this paper, we present a way of optimizing the cancellation path modern in order to enhance the convergence speed by introducing intentional phase error. Carefully designed intentional phase error enhances the convergence speed of the Filtered X LMS algorithm for pure tone noise suppression application without any performance loss at steady state.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.12
• /
• pp.2503-2510
• /
• 2002

Since the first shape-form-shading technique was developed by Horn in the early 1970s, many different approaches have been continuously emerging in the past three decades. Some of them improve existing techniques, while others are completely new approaches. Using the image reflectance equation, they estimate the 3-D shape of an object utilizing adequate constraints. Each algorithm applies different constraints such as brightness, smoothness, and integrability to solve the shape-from-shading problem. Especially for symmetric objects, a symmetry constraint is proposed to improve the performance of existing shape-from-shading algorithm in this paper. The symmetry constraint is imposed to a conventional algorithm and then the improvement in the performance of 3-D shape reconstruction is proved by quantitatively comparing the depth and gradient errors.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.5
• /
• pp.2171-2185
• /
• 2020

In order to judge that whether the vehicles in different images which are captured by surveillance cameras represent the same vehicle or not, we proposed a novel vehicle face recognition algorithm based on improved Nonnegative Matrix Factorization (NMF), different from traditional vehicle recognition algorithms, there are fewer effective features in vehicle face image than in whole vehicle image in general, which brings certain difficulty to recognition. The innovations mainly include the following two aspects: 1) we proposed a novel idea that the vehicle type can be determined by a few key regions of the vehicle face such as logo, grille and so on; 2) Through adding weight, sparseness and classification property constraints to the NMF model, we can acquire the effective feature bases that represent the key regions of vehicle face image. Experimental results show that the proposed algorithm not only achieve a high correct recognition rate, but also has a strong robustness to some non-cooperative factors such as illumination variation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1999.10a
• /
• pp.309-312
• /
• 1999

This paper proposed a novel method for pseudo-on-line scheme using look-up table based on the genetic algorithm The technique is an pseudo-on-line method that optimally estimate the parameters of FPID controller for systems with non-linearity using the genetic algorithm which does not use the gradient and finds the global optimum of an unconstraint optimization problem. The proposed controller is applied to speed control of 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed method is more excellent then conventional FPID and PID controllers.