This paper proposes a High Performance Full-Swing BiCMOS (HiF-BiCMOS) circuit which improves on the conventional BiCMOS circuit. The HiF-BiCMOS circuit has all the merits of the conventional BiCMOS circuit and can realize full-swing logic operation. Especially, the speed of full-swing logic operation is much faster than that of conventional full-swing BiCMOS circuit. And the number of transistors added in the HiF-BiCMOS for full-swing logic operation is constant regardless of the number of logic gate inputs. The HiF-BiCMOS circui has high stability to variation of environment factors such as temperature. Also, it has a preamorphized Si layer was changed into the perfect crystal Si after the RTA. Remarkable scalability for power supply voltage according to the development of VLSI technology. The power dissipation of HiF-BiCMOS is very small and hardly increases about a large fanout. Though the Spice simulation, the validity of the proposed circuit design is proved.

VLIW architecture capable of testing multiple conditions in a cycle must support an efficient mechanism for multi-way branches. This paper proposes a mechanism to speed up the execution of multi-way branches and an efficient memory packing method of instructions, which reduced the wasted memory space. Also, we develops a new compiler technique which can transform program segments that are not applied to multi-way branches into ones that are applied to multi-way branches. The benefits gained by the transformation are to reduce branch penalty and to increase instruction-level parallelism.

In this paper, a VlSI architecture for Reed-Solomon (RS) decoder based on the Berlekamp algorithm is proposed. The proposed decoder provided both erasure and error correcting capability. In order to reduc the chip area, we reformulate the Berlekamp algorithm. The proposed algorithm possesses a recursive structure so that the number of cells for computing the errata locator polynomial can be reduced. Moreover, in our approach, only one finite field multiplication per clock cycle is required for implementation, provided an improvement in the decoding speed, and the overall architecture features parallel and pipelined structure, making a real time decoding possible. From the performance evaluation, it is concluded that the proposed VLSI architecture is more efficient in terms of VLSI implementation than the rcursive architecture based on the Euclid algorithm.

It is well know that the tuning method of Yuwana-Seborg (1982) can not be even applied to the relatively small delay system due to the phase errors from the Pad approximation suh (1984, 85, 86). Jutan and Rodriguez(1984), lee(1989), Chen(1989), Lee and Edgar(1990), etc have been tried to improve it. In this stydy, such recent results and their problems are investigated. A new tuning method by "a frequency scale transformation". which is based on a previous result of Suh(1984). is proposed. It can reduce the magnitude of the phase error significantly.

Recently, the elimination of speed sensors has been one of the important requirement in vector control systems, because the speed sensor spoil the ruggedness and simplicity of induction motor. This paper proposes sensorless vector control for high performance of induction motor. The proposed vector control scheme is based on a rotor flux and speed which are calculated from the stator voltage and currents with improved flux estimator. The characteristics of vector control employing stator voltage and current generally deteriorate as the speed gets lower acause the calculated rotor flux depends on the stator resistance and it is difficult to calculate rotor flux at low speed of standstill. This new control system is robust with respect to variations of the stator resistance and it makes possible to calculated rotor flux at low speed of standstill. These feature are verified by the simulation results.

This paper is to design an autobalancing system based-on microprocessor for hemodiafiltration (HDF) system. The proposed system consist of motor control part, thermostatic control part, alarm system and electronic scale which ar automatically controlled by microprocessor. Conventional hemodialysis system can not remove medium molecular articles but hemodialysis system with the proposed system can remove and infuse substitute to the patient. This system can be easily interfaced with any other conventional HD system. The results obtained from performance evaluation of the proposed system are suitable for clinical supporting system.

This paper presents the design consideration of the MFNNs(Multilayer Feed forward Neural Networks) based on the distribution of the given teching patterns. By extracting the feature points from the given teaching patterns, the structure of a network including the netowrk size and interconnection weights of a network is initialized. This network is trained based on the modified version of the EBP(Error Back Propagation) algorithm. As a result, the proposed method has the advantage of learning speed compared to the conventional learning of the MFNNs with randomly chosen initial weights. To show the effectiveness of the suggested approach, the simulation result on the approximation of a two demensional continuous function is shown.

This paper presents an analog circuit implementation and experimental resuls of the Hopfield type neural network. The proposed architecture enables the reconfiguration betwewn feedback and feedforward networks and employs new circuit designs for the weight supply and storage, analog multilier, nd current-voltage converter, in order to achieve area efficiency as well as function al versatility. The layout design of the eight-neuron neural network is tested as an associative memory to verify its applicability to real world.

This paper presents methodology which enables the derivation of goal ordering rules from the analysis of problem failures. We examine all the possible ways of taking actions that lead to failures. If there are restrictions imposed by a problem state on possible actions to be taken, the restrictions manifest themselves in the form of a restricted set of possible operator bindings. Our method makes use of this observation to derive general control rules which are guaranteed to be correct. The overhead involved in learning is very low because this methodology needs only small amount of data to learn from namely, the goal stacks from the leaf nodes of a failure search tree. Empirical tests show that the rules derived by our system PAL couperform those derived by other systems such as PRODIGY and STATIC.

Calibration of Engine models is a painstaking process but very important for successful application to automotive industry problems. A combined heuristic and machine learning approach has therefore been adopted to improve the efficiency of model calibration. We developed an intelligent calibration program called ICALIB. It has been used on a daily basis for engine model applications, and has reduced the time required for model calibrations from many hours to a few minutes on average. In this paper, we describe the heuristic control strategies employed in ICALIB such as a hill-climbing search based on a state distance estimation function, incremental problem solution refinement by using a dynamic tolerance window, and calibration target parameter ordering for guiding the search. In addition, we present the application of amachine learning program called GID3*for automatic acquisition of heuristic rules for ordering target parameters.

The transfer function of vector-controlled induction motor is represented along with both unstructured and structured uncertainty such as the error of rotor time constant and current ripple. The low-pass-filter behavior of a magnetizing inductance gets rid of unstructured uncertainty in the transfer function. The robust controller to compensate variation of the transfer function is designed using simple P-I linear controllers. The coefficients of speed PI controller are determined from an overshoot and a rising time of system and the coefficients of model-following PI controller are obtained using the solution of Riccati equation of LQR control in the state space equation of the error system. Experimental results with the DSP-based model-following robust controller are shown a good robustness against the structured uncertainty of the motor.