In this paper the projective controls, previously derived to preserve the dynamic modes of a state-feedback reference system, are extended to allow the preservation of the modes of a general output-feedback reference system. In general, the extension allows projective controls to be used as a controller approximation technique, where a reduced-order controller is designed to approximate the closed-loop behavior of the higher-order reference controller. This extension is useful if the best available reference control for the system is an output-feedback control. An example shows that the increased design freedom of proposed design method allows the stabilization of a given plant using a lower-order controller than the projective controls with state-feedback reference.

In the hypercube multiprocessor system. repeated allocations and deallocations of subcubes generate a fragmented hypercube from which. even if sufficient free processors are available, a subcube that is large enough to accomodate a new task cannot be formed. To eliminate the fragmentation, we need a processor relocation to move a task-occupied subcube to a free subcube, and gather dispersed small subcubes. In this paper, we propose a routing algorithm for task migration in circuit- switched hypercube to relocate processors. In the circuit-switched hypercube, we have to find a set of dedicated link-disjoint routing paths for each node to move a task from a busy subcube to a free subcube in fragmentation. The proposed algorithm is based on the PGC(packed Gray code) which detects all kinds of subcubes.

In this paper, we compare several methods for implementing a VHDL design database through a case study on VHDL tool development system. We implemented three versions of the VHDL design database which the VHDL tool development system is based on. The first version was coded in the C programming language following value-oriented paradigm. The second one was coded in the C++ programming language following object-oriented paradigm. The third one was implemented using an existing object-oriented database. Based on our experience, we present quantitatively the pros and cons of each implementation method. The value-oriented version was most difficult to implement but showed good performance. Compared to the value- oriented version, the C++ version was twice as easy to implement and showed about the same performance. Using an existing object-oriented database allowed easiest implementation but resulted in a 1.5 to 6 times slower version.

In this paper, we propose a range image segmentation algorithm using robust regression. We derive a least $\kappa$th-order square (LKS) method by generalizing the least median of squares (LMedS) method and compare it with the conventional robust regressions. The LKS is robuster against outliers than the LMedS and shows performance similar to the residual consensus (RESC). The RESC uses the predetermined number of sorted residuals, whereas the LKS uses an adaptive parameter determined by given observations rather than the a priori knowledge. Computer simulation with synthetic and real range images shows that the proposed LKS algorithm gives better performance than the conventional ones.

In this paper, we propose a new algorithm, so called the Signal Decorrelation via Virtual Translation of Array (SDVTA) algorithm, for estimating the directions of arrival(DOA's) of narrowband coherent signals incident on a general array. An effective procedure is composed of transforming the steering matrix of the original array into that of the virtually translated sensor array and taking the average of the transformed covariance matrices in order to decorrelate the coherent signals. The advantage of this approach is in that 1) it can estimate the DOA's of m-1 coherent signals(M : the number of array sensors) since the effective aperture size is never reduced. 2) a geometry of array is unrestricted for solving the narrowband coherency problem. 3) the efficiency of signal decorrelation does not depend on the phase differences between coherent signals unlike the Coherent Signal Subspace Method (CSM). Simulation results are illustrated to demonstrate the superior performance of this new algorithm in comparison with the normal MUSIC and examine the comparative performance with the various choices of the optimal transformation matrix under coherent signal environments.

In This Paper, Linearization problem is discussed to reduce distortion of a nonlinear system based on Schetzen's pth-orfer inverse theorem. We propose a nonlinear adaptive prefiltering algorithm which can reduse nonlinear distortion up to pth order by tandemly connecting a pth-order Volterra filter before the nonlinear system under the consideration and by adjusting the filter coefficients adaptively. The feasibility of applying the proposed algorithm to a nonlinear system is conformed via computer simulation by observing significant reduction of total nonlinear distortion for the case of random input and sinusoidal input excitation.

An intelligent trajectory control method that controls a direction and a average velocity for a prosthetic arm by force and direction estimations using EMG signals is proposed. 3 stage linear filters are used as a real time joint trajectory planner to minimize the impact to human body induced by arm motions and to reduce muscle fatigues. We use combination of MLP and fuzzy filter for a limb direction estimation and a time model of force for determining a cartesian trajectory control parameter. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. Simulation results of the proposed method show that the arm is effectively followed the desired trajectory by estimated foreces and directions. This method reduces the number of electrodes and attatched sites compared with the method using Hogan's impedance control.

In this paper, we realize a real time digital FM synthesizer based on genetic algorithm using a general purpose digital signal processor. Especially, we synthesize diverse music sounds nicely using a synthesis model consisting of a single modulator and multiple carriers. Also we present genetic algorithm-based technique which determines optimal parameters for reconstruction through FM synthesis of a sound after analyzing the spectrum of PCM data as a standard music sound using FFT. Using the suggested parameter extractiuon algorithm, we extract parameters of several instruments and then synthesize digital FM sounds. To verify the validity of the parameter extraction algorithm as well as realization of a real time digital music synthesizer, the evaluation is first done by listening the sound directly as subjective test. Secondly, to evaluate the synthesized sound objectively with an engineering sense, we compare the synthesized sound with an original one in a time domain and a frequency domain.

In this paper, a band-pass filter is implemented with the diffusion and difference processes by using the diffusion neural network model. The center frequency of this band-pass filter can be varied by iterations of the diffusion and difference operations, and the selectivity can be determined by iterations of the difference operation. We propose an efficient algorithm that can generate various band-pass filters using arbitrary diffusion and difference iterations. This algorithm needs only simple operations of diffusion and difference.