In some practical applications of the LMS Algorithm the coefficient adaptation can be performed only after some fixed delay. The resulting algorithm is known as the Delayed Least Mean Square (DLMS) algorithm in the literature. There exist analyses for this algorithm, but most of them are based on the unrealistic independence assumption between successive input vectors. Inthis paper we consider the DLMS algorithm with decreasing step size .mu.(n)=n/a, a>0 and prove the almost-sure convergence ofthe weight vector W(n) to the Wiener solution W$_{opt}$ as n .rarw. .inf. under the mixing unput condition and the satisfaction of the law of large numbers. Computer simulations for decision-directed adaptive equalizer with decoding delay are performed to demonstrate the functioning of the proposed algorithm.m.

It is not yet possible to solve the optimal number of neurons in hidden layer at neural networks. However, it has been proposed and proved by experiments that there is a limit in increasing the number of neuron in hidden layer, because too much incrememt will cause instability,local minima and large error. This paper proposes a module neural controller with pattern recognition ability to solve the above trade-off problems and to obtain fast learning convergence speed. The proposed neural controller is composed of several module having Multi-layer Perrceptron(MLP). Each module have the less neurons in hidden layer, because it learns only input patterns having a similar learning directions. Experiments with six joint robot manipulator have shown the effectiveness and the feasibility of the proposed the parallel module neural controller with pattern recognition perceptron.

In this paper, a new method is proposed where the vision and ultrasonic sensor are used to recognize obstacles and to obtain its position and size. Ultrasonic snsors are used to obtain the actual navigation path width of the mobile robot. In conjunction with camera images of the path, recognition of obstacles and the determination of its distance, direction, and width are carried out. The characteristics of the sensors and the mobile robots used generally make it difficult to recognize all environments; accordingly, a restricted environment is employed for this study.

In this paper, we present a message transfer scheme for efficient message passing in the hierarchically structured multiprocessor computer SPAX(Scalable Parallel Architecture computer based on X-bar network). The message transfer scheme provides interface not only with operating system but also with end users. In order to transfer two types of control message and data message efficiently, it supports both of memory-mapped transfer and DMA-based transfer. Dual-port RAMs are used as message buffers, and control and status registers provide efficient programming interface. Interlaced parity scheme is adopted for error control. If any error is detected at receiving node, errored packet is resent by sender according to retry mechanism. In conjunction with retry mechanism, watchdog timers are used to protect infinite waiting and repeated retry. The proposed message transfer scheme can be applied to input/output nodes and communication connection nodes as well as processing nodes in the SPAX.

In this paper, we present a 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In object modeling step, the features for recognition are extracted from the CAD models of objects to be recognized. Since the approach is based on the CAD models, the accuracy and flexibility are greatly improved. In matching stage, the sensed image is compared with the stored model, which is assumed to yield a distortion (location and orientation) in the 3-D Hough transform domain. The high dimensional (6-D) parameter space, which defines the distortion, is decomposed into the low dimensional space for an efficient recognition. At first we decompose the distortion parameter into the rotation parameter and the translation parameter, and the rotation parameter is further decomposed into the viewing direction and the rotational angle. Since we use the 3-D Hough transform domain of the input images directly, the sensitivity to the noise and the high computational complexity could be significantly alleviated. The results show that the proposed 3-D object recognition system provides a satisfactory performance on the real range images.

In video camera, an automatic video quality compensation method using the dynamic range transform is proposed. The histogram is used to decide the nonuniformness of picture brightness by nonuniform lighting. The gray level is divided four regions, and the histogram is obtained per one field. We introduce a new parameter, nonuniformness, defined by the cumulative difference between its CDF and LCDF. We also propose the decision function of the dynamic range transform constant versus its nonuniformness, and compensate the quality of video automatically.

This paper describes an algorithm that reduces computational requirement of the Kalman filter and estimates the signal efficiently. The reference signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be smaller than that in the time domain. In the wavelet transform domain the autocorrelation matrix is nearly diagonal. Therefore, the transformed signal can be decomposed each orthogonal elements. The Kalman filter can be applied to each orthogonal elements and computational requirement is reduced. The possibility of applying the parallel Kalman filter was verified through the theory and simulation. The eigenvalue spread in the wavelet transform domain is smaller 8.35 times than that in the time domain and the computational requirement is reduced from 1.4 times to 2. 93 times than that of the conventional Kalman filter.

We present an optimized integer cosine transform(OICT) as an alternative approach to the conventional discrete cosine transform(DCT), and its fast computational algorithm. In the actual implementation of the OICT, we have used the techniques similar to those of the orthogonal integer transform(OIT). The normalization factors are approximated to single one while keeping the reconstruction error at the best tolerable level. By obtaining a single normalization factor, both forward and inverse transform are performed using only the integers. However, there are so many sets of integers that are selected in the above manner, the best OICT matrix obtained through value minimizing the Hibert-Schmidt norm and achieving fast computational algorithm. Using matrix decomposing, a fast algorithm for efficient computation of the order-8 OICT is developed, which is minimized to 20 integer multiplications. This enables us to implement a high performance 2-D DCT processor by replacing the floating point operations by the integer number operations. We have also run the simulation to test the performance of the order-8 OICT with the transform efficiency, maximum reducible bits, and mean square error for the Wiener filter. When the results are compared to those of the DCT and OIT, the OICT has out-performed them all. Furthermore, when the conventional DCT coefficients are reduced to 7-bit as those of the OICT, the resulting reconstructed images were critically impaired losing the orthogonal property of the original DCT. However, the 7-bit OICT maintains a zero mean square reconstruction error.

The purpose of this paper is to build a computer vision system that endows an autonomous mobile robot the ability of automatic measuring of the analog and digital meters installed in nuclear power plant(NPP). This computer vision system takes a significant part in the organization of automatic surveillance and measurement system having the instruments and gadzets in NPP under automatic control situation. In the meter image captured by the camera, the meter area is sorted out using mainly the thresholding and the region labeling and the meter value recognition process follows. The positions and the angles of the needles in analog meter images are detected using the projection based method. In the case of digital meters, digits and points are extracted and finally recognized through the neural network classifier. To use available database containing relevant information about meters and to build fully automatic meter recognition system, the segmentation and recognition of the function-name in the meter printed around the meter area should be achieved for enhancing identification reliability. For thus, the function- name of the meter needs to be identified and furthermore the scale distributions and values are also required to be analyzed for building the more sophisticated system and making the meter recognition fully automatic.

In on-line character recognition, to segment input character is important. This paper proposes an internal character segmentation algorithm. The internal segmentation algorithm produces candidate words by considering possible combinations of Korean alphabets. In this process, we make use of projections of strokes onto the horizontal axis to remove ambiguities among candidate words. As a result of experiments, the internal segmentation algorithm shows better performance than external segmentation algorithm as the gap between sample characters becomes smaller.

A forced commutated cycloconverter (FCC) is a direct ac-ac converter capable of providing simultaneous voltage and frequency transformations. In this paper, vector control of an induction motor controlling stator current with forced commutated cycloconverter is presented. The advantage of current control is that the stator dynamics are eliminated and high performance vector control can be achieved. A novel modulation method based on dq transformation techniques is presented. Proposed modulation strategy generates the low frequency modulation function by the instantaneous value of the desired output voltages not by the steady state values of output magnitude and output frequency. PI control and predictive control algorithm for current control are applied, and the validity of proposed method is confirmed through digital simulations. Simulation results of step response and torque distubance and current control are presented.