Multimedia mobile communication systems with high-speed radio transmission supported by asynchronous transfer mode (ATM) technologies have been intensively studied over the last few years. Smaller radio zones termed microcells and picocells will be used in this kind of mobile communication systems for the purpose of high-speed radio transmission. When the coverage of a radio zone is smaller, the amount of traffic per radio zone is relatively low. It is not possible to use the cable circuits connecting the switch and base stations in an efficient manner because of the lack of the scale effect of traffic. With smaller radio zones, moreover, handoff occurs frequently as a mobile station moves. The switch is required a large capacity to handle the processing of frequent handoffs. This paper proposes a mobile network architecture controlled by the concentrated grouping of base stations. A special feature of this configuration is the ability of the network's switches to efficiently accommodate numerous base stations that control small radio zones. It can also lighten the handoff control load of switches; the effect of handoff frequency reduction is evaluated with computer simulation.

We theoretically evaluate the prediction efficiency of the overlapped block motion compensation (OBMC) compared with the conventional non-overlapped approach. Based on the one-dimensional signal model characterized by the AR(1) process and first-order polynomial motion, a condition under which the performance of the OBMC is better, and an optimum window function are derived. From the results, we discuss and analyze several properties of the OBMC, some of which have been experimentally reported in the literature.

In this paper, a general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived and implemented with simplified probabilistic models. The formula is the generalized probabilistic diffusion equation based on Bayesian model, and can be implemented into some different forms corresponding to the probabilistic models in the disparity neighborhood system or configuration. The probabilistic models are independence and similarity among the neighboring disparities in the configuration. The independence probabilistic model guarantees the discontinuity at the object boundary region, and the similarity model does the continuity or the high correlation of the disparity distribution. According to the experimental results, the proposed algorithm had good estimation performance. This result showes that the derived formula generalizes the probabilistic diffusion based on Bayesian MAP algorithm for disparity estimation. Also, the proposed probabilistic models are reasonable and approximate the pure joint probability distribution very well with decreasing the computations to O(n()) from O(n()4) of the generalized formula.

The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interaction (HCI). In particular, visual interpretation of hand gestures can help achieve easy and natural comprehension for HCI. Many methods for hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network (NN), and hidden Markov model (HMM)s. In our research, HMMs are proposed for alphabetical hand gesture recognition. In the preprocessing stage, the proposed approach consists of three different procedures for hand localization, hand tracking and gesture spotting. The hand location procedure detects the candidated regions on the basis of skin color and motion in an image by using a color histogram matching and time-varying edge difference techniques. The hand tracking algorithm finds the centroid of a moving hand region, connect those centroids, and produces a trajectory. The spotting algorithm divides the trajectory into real and meaningless gestures. In constructing a feature database, the proposed approach uses the weighted ρ-φ-ν feature code, and employ a k-means algorithm for the codebook of HMM. In our experiments, 1,300 alphabetical and 1,300 untrained gestures are used for training and testing, respectively. Those experimental results demonstrate that the proposed approach yields a higher and satisfactory recognition rate for the images with different sizes, shapes and skew angles.

In this paper, we consider the Integrate-and-Fire Model (ab. IFM) with two periodic inputs. The IFM outputs a pulse-train which is governed by a one dimensional return map. Using the return map, the relationship between the inputs and the output is clarified: the first input determines the global shape of the return map and the IFM outputs various periodic and chaotic pulse-trains; the second input quantizes the state of the return map and the IFM outputs various periodic pulse-trains. Using a computer aided analysis method, the quantized return map can be analyzed rigorously. Also, some typical phenomena are confirmed in the laboratory.

This paper treats a fault detection/location of multi-processor systems, and we present a checking scheme based on Modified Processor-Data (MPD) graph with considering an error generation/propagation model for Algorithm-Based Fault Tolerant (ABFT) systems. The error propagation model considered here allows a computation result with multiple (more than one) erroneous inputs to be either erroneous or error-free. Also a basic algorithm for constructing checks for single-fault locatable/two-fault detectable ABFT systems based on the checking scheme is described with design examples.

Low-voltage technique for IC is getting one of the most important matters. It is quite difficult to realize a filter which can operate at 1 V or less because the base-emitter voltage of transistors can hardly be reduced. A design of a low-voltage continuous-time filter is presented in this paper. The basic building block of the filter is a pseudo-differential transconductor which has no tail current source. Therefore, the operating voltage is lower than that of an emitter-coupled pair. However, the common-mode (CM) gain of the transconductor is quite high and the CMRR is low. In order to reduce the CM gain, a CM feedback circuit is employed. The transconductance characteristic is expressed as the function of hyperbolic cosine. The designed filter is a fifth-order gyrator-C filter. The transconductor and the filter which has a fifth-order Butterworth lowpass characteristic are demonstrated by PSpice simulation. Transconductance characteristic, CMRR and stability of the transconductor are confirmed through the simulation. In the analysis of the filter, frequency response and offset voltage are examined. It is shown that the filter which has corner frequency of the order of megahertz can operate at a 1 V supply voltage.

In this paper, a new digital chaos circuit which can generate multiple-scroll strange attractors is proposed. Being based on the piecewise-linear function which is determined by on-chip supervised learning, the proposed digital chaos circuit can generate multiple-scroll strange attractors. Hence, the proposed circuit can exhibit various bifurcation phenomena. By numerical simulations, the learning dynamics and the quasi-chaos generation of the proposed digital chaos circuit are analyzed in detail. Furthermore, as a design example of the integrated digital chaos circuit, the proposed circuit realizing the nonlinear function with five breakpoints is implemented onto the FPGA (Field Programmable Gate Array). The synthesized FPGA circuit which can generate n-scroll strange attractors (n=1, 2, 4) showed that the proposed circuit is implementable onto a single FPGA except for the SRAM.

In this paper, near real time digital radiography system was implemented for the automatic verification of local errors between simulation plan and radiation therapy. Portal image could be acquired through video camera, image board and PC after therapy radiation was converted into light by a metal/fluorescent screen. Considering the divergence according to the distance between the source and the plate, we made a 340 340 12 cm3 basis point plate on which five rods of 4 cm height and 8 mm diameter lead (Pb) were built to display reference points on the simulator and the portal image. We converted the portal image into the binary image using the optimal threshold value which was gotten through the histogram analysis of the acquired portal image using the basis point plate. we got the location information of the iso-center and basis points from the binary image, and removed the systematic errors which were from the differences between the simulation plan and the portal image. Field size which was measured automatically by optimal threshold portal image, was verified with simulation plan. Anatomic errors were automatically detected and verified with the normalized simulation and the portal image by pattern matching method after irradiating a part of the radiation. Therapy efficiency was improved and radiation side effects were reduced by these techniques, so exact radiation treatment are expected.

In this paper, by making good use of the parallel-transit-evaluation algorithm and sparsity of the connection between neurons, a pipeline structure is successfully introduced to the sequential Boltzmann machine processor. The novel structure speeds up nine times faster than the previous one, with only the 12% rise in hardware resources under 10,000 neurons. The performance is confirmed by designing it using 1.2 µm CMOS process standard cells and analyzing the probability of state-change.

In this paper an analysis on the oversampling data recovery circuit is presented. The input waveform is assumed to be non-return-zero (NRZ) binary signals. A finite Markov chain model is used to evaluate the steady-state phase jitter performance. Theoretical analysis enables us to predict the input signal-to-noise ratio (SNR) versus bit error rate (BER) of the oversampling data recovery circuit for various oversampling ratios. The more number of samples per single bit results in the better performance on BER at the same input SNR. To achieve 10-11 BER, 8 times oversampling has about 2 dB input signal penalty compared to 16 times oversampling. In an architectural choice of the oversampling data recovery circuit, the recovered clock can be updated in each data bit or in every multiple bits depending on the input data rate and input noise. Two different clock update schemes were analyzed and compared. The scheme updating clock in every data bit has about 1.5 dB penalty against the multiple bits (4 bits) clock updating scheme with 16 times oversampling in white noise dominant input data. The results were applied to the fabricated circuits to validate the analysis.

In this paper, quasi-Gaussian filter, quasi-median filter and locally adaptive filters are introduced. A new adaptive vector filter based on noise estimate is proposed to suppress Gaussian and/or impulse noise. To estimate the type and degree of noise corruption, a noise detector and an edge detector are introduced, and two key parameters are obtained to characterize noise in color image. After globally estimating the type and degree of noise corruption, different locally adaptive filters are properly chosen for image enhancement. All noisy images, used to test filters in experiments, are generated by PaintShopPro and Photoshop software. Experimental results show that the new adaptive filter performs better in suppressing noise and preserving details than the filter in Photoshop software and other filters.

In this paper, we present two fast motion estimation techniques with adaptive variable search range using spatial and temporal correlation of moving pictures respectively. The first technique uses a frame difference between two adjacent frames which is used as a criterion for deciding search window size. The second one uses deviation between the past and the predicted current frame motion vectors which is also used as a criterion for deciding search window size. Simulation results show that these methods reduce the number of checking points while keeping almost the same image quality as that of full search method.

We propose a motion estimation algorithm using less gray level images, which are composed of bits pixels lower than 8 bits pixels. Threshold values for generating low bits pixels from 8 bits pixels are simply determined as median values of pixels in a macro block. The proposed algorithm reduces the computational complexity of motion estimation at less expense of video quality. Moreover, median cut quantization can be applied to multilevel images and combined with a lot of fast algorithms to obtain more effective algorithms.

A new motion analysis method and an image restoration process for removing motion blur are proposed. Motion analysis includes the motion estimation and motion-based segmentation. Based on the analysis, we can obtain an image divided into multiple segments with different point spread functions. For removing motion blur, we propose an image degradation model for the motion with an arbitrary direction and a regularized iterative restoration method. By using the proposed degradation model and the restoration method, we can efficiently remove the space-variant motion blur.

This paper presents a new method for image interpolation based on truncated projections onto convex sets (POCS). By using the convergence property to properly defined convex sets, the proposed algorithm can restore high frequency details in the original high resolution image. In order to apply the POCS method to the interpolation procedure, we first present a two-dimensional separable image degradation model for a low resolution imaging system. According to the model, we propose a truncated POCS-based spatial interpolation algorithm for image sequences. Experimental results with synthetic and real image sequence show that the proposed algorithm gives indiscernible interpolation performance compared with the conventional POCS-base algorithm, while it significantly reduces computational complexity and is suitable for processing image sequences.

This paper proposes an analysis method of the roundoff error due to finite-wordlength decoding in fractal image coding. The proposed method can be applied to large images such as 256 256 or 512 512 images because it needs no complex matrix computation. The simplified model used here ignores the effect of decimation ratio on the roundoff error because it is negligible. As an analysis result, the proposed method gives the output error variance which consists of grey-tone scaling coefficients and an iteration number. This method is tested on various types of 12 standard images which have 256 256 size or 512 512 size with 256 grey levels. Comparisons of simulation results with analysis results are given. The results show that our analysis method is valid for the fractal image coding.

This research presents a novel analytic model to predict the instruction execution rate of superscalar processors using the queuing model with finite-buffer size and synchronous operation mode. The proposed model is also able to analyze the performance relationship between cache and pipeline. The proposed model takes into account various kinds of architectural parameters such as instruction-level parallelism, branch probability, the accuracy of branch prediction, cache miss, and etc. To prove the correctness of the model, we performed extensive simulations and compared the results with the analytic model. Simulation results showed that the proposed model can estimate the average execution rate accurately within 10% error in most cases. The proposed model can explain the causes of performance bottleneck which cannot be uncovered by the simulation method only. The model is also able to show the effect of the cache miss on the performance of out-of-order issue superscalar processors, which can provide an valuable information in designing a balanced system.

Hawkins noise model is modified for HBT application. The non-ideal ideality factor of HBT is included in both dynamic resistance and noise figure equations. Emitter resistance is also included. The extraction method of noise resistance Rn is developed. Based on the method, a simple analytic equation of Rn is derived and experimentally verified. The effects of noise sources on minimum noise figure are analyzed. The dominant noise sources are the shot noises of emitter and collector currents. Generally, when the minimum noise figure is measured at various current levels, there exists an current level at which the slope of minimum noise figure curve is zero. The zero slope current level coincides with the current level at which the noise contribution of the emitter and collector shot noises including the cancellation by correlation of two sources is minimum. Parasitic resistance degrades output noise through the shot noise amplification with a minor effect of the thermal noise of itself.

In this paper, a novel variable-rate vector quantizer (VQ) design algorithm using fuzzy clustering technique is presented. The algorithm, termed fuzzy entropy-constrained VQ (FECVQ) design algorithm, has a better rate-distortion performance than that of the usual entropy-constrained VQ (ECVQ) algorithm for variable-rate VQ design. When performing the fuzzy clustering, the FECVQ algorithm considers both the usual squared-distance measure, and the length of channel index associated with each codeword so that the average rate of the VQ can be controlled. In addition, the membership function for achieving the optimal clustering for the design of FECVQ are derived. Simulation results demonstrate that the FECVQ can be an effective alternative for the design of variable-rate VQs.