This paper examines the feasibility of a high frequency (moro than 1 GHz) ring-oscillator-type CMOS VCO, able to maintain a good linearity between the oscillator output frequency and control voltage, while preserving low voltage and low power operation capabilities. A CMOS VCO circuit, with a newly developed corrent-controlled delay cell and an architecture combining the transitions of each delay cell output, with high-frequency operation, was designed and simulated using the CMOS 0.6 µm device paramenters. We analyzed the generation of unnecessary harmonics and sub-harmonics when a delay cell's propagation delay time varied. The simulation indicated that a CMOS VCO with a frequency range of 200 MHz to 1.4 GHz, a power dissipation of 8.5 mW at 900 MHz from a 3 V power supply, and an operation voltage of 1 V to 3 V can be implemented on a chip.

This paper is described on the realization of simulated inductance cercuit with parallel negative conductance and its application for an oscillator. The design's condition for realizing the circuit needs stability, narrow expance of elements, larger dynamic-range and lower sensitivity. A new floating simulated inductance circuit with parallel nagative conductance with two operational amplifiers, four resistors, and four capacitors is created by using the design's algorithm. And the elements sensitivity of the simulated circuit is superior to that of the conventional circuits. By experimenting with a resonance circuit, the author tested the sinusoidal oscillator's circuit of a parallel -GLC as an application in order to confirm the operation of the simulated inductance circuit with parallel negative conductance.

A filter configuration that allows configuration of any transfer function used the state variable is discribed as an application of the second generation current conveyors (CCIIs) to RC networks. The filter types discussed are low-pass filter (LPF), high-pass filter (HPF), band-pass filter (BPF), all-pass filter (APF), and band-elimination filter (BEF). The filter circuit consists of four CCIIs and allows tandem connections. The device sensitivity and CCII's sensitivity to transfer coefficient are relatively low. The filter circuit that allow simultaneous configuration wewe fabricated. An experimental result at around 10kHz was obtained for the filters. In the case, the LPF, HPF, BPF, APF, and BEF characteristics are obtained at Q value of 5.0.

We have shown a non-invasive method for estimating transient changes in aortic flow and ventricular volume based on optimal control theory by using successful simulations of reported experimental data. The performance function to evaluate the optimality of the cardiovascular system was proposed based oh physical, fluid mechanical and pathophysiological considerations. It involved the work of the ventricle, the rate of changes in the aortic flow and the ventricular pressure. We determined that the cardiovascular system operates optimally when the performance function has been minimized. The relative magnitudes of the reductions of changes in these terms were expressed by the weighting coefficients. The arterial system was described by the Wind Kessel model using arterial resistance, aortic compliance and aortic valvular resistance. We set boundary conditions and transitional conditions derived from the systolic and diastolic phases of the aortic flow and the arterial pressure. The optimized system equations were converted to 6 linear simultaneous differential equations with 6 boundary conditions. The optimal ventricular pressure and aortic flow rate that minimize the performance function were obtained by solving these differential equations. By alternating the weighting coefficients of the work of ventricle and the rate of change in the ventricular ejection pressure, successful simulations of the ventricular pressures recorded from human subjects and those from isolated canine ventricle were obtained. Once the sets of weighting coefficients had been determined by successful simulations of ventricular pressures, the calculated aortic flow curves and pressure volume loops by the present method coincided with the reported experimental data. The changes in ventricular pressure and aortic flow produced by alternating the weighting coefficients to simulate the reported ventricular pressures and aortic flow curves under the different afterload conditions were consistent with biophysical experimental data. The present method is useful to estimata aortic flow curve and ventricular pressure volume loops non-invasively.

In this letter, we propose an adaptive multiuser receiver using a Hopfield network for code-division multiple-access communications and its performance is compared with that of the other types of multiuser receiver via computer simulation. The proposed adaptive receiver estimates both the signal amplitudes and spreading sequences for all the users using training data.

This paper describes the results of tests that measured the allowable delay between images and tactile information via a force feedback device. In order to investigate the allowable delay, two experiments were performed: 1) subjective evaluation in real space and 2) subjective evaluation in virtual space using a force feedback device.

We proposed a new thchnique using saw wave modulation light to measure the thermal diffusivity of a transparent adhesive by photoacoustic microscope. In this technique, the time required for the measurement of it can be reduced by one-fifth compared with that of a conventional method.

We reveal fundamental electromagnetic characteristics of a basic proposition of the security tag system, being able to exclude a misjudgment caused by a neighboring reflective object, provided with a correlative detection, and that with a multi-resonant tag.

A new adaptive AR spectral estimation method is proposed. While conventional least-squares methods use a single windowing function to analyze the linear prediction error, the proposed method uses a different window for each frequency band of the linear prediction error to define a cost function to be meinemized. With this approach, since time and frequency resolutions can be traded off throughout the frequency spectrum, an improvement on the precision of the estimates is achieved. In this paper, a wavelet-like time-frequency resolution grid is used so that low-frequency components of the linear prediction error are analyzed through long windows and high-frequency components are analyzed through short ones. To solve the optimization problem for the new cost function, special properties of the correlation matrix are used to derive an RLS algorithm on the order of M², where M is the number of parameters of the AR model. Computer simulations comparing the performance of conventional RLS and the proposed methods are shown. In particular, it can be observed that the wavelet-based spectral estimation method gives fine frequency resolution at low frequencies and sharp time resolution at high frequencies, while with conventional methods it is possible to obtain only one of these characteristics.

We present a new method for the identification of time-invariant multichannel autoregressive (AR) processes corrupted by additive white observation noise. The method is based on the Yule-Walker equations and identifies the autoregressive parameters from a finite set of measured data. The input signals to the underlying process are assumed to be unknown. An inverse filtering technique is used to estimate the AR parameters and the observation noise variance, simultaneously. The procedure is iterative. Computer simulation results that demonstrate the performance of the identification method are presented.

This paper proposes a new lossless data compression method, which utilizes a context sorting algorithm. Every symbol in the data can be predicted by taking its immediately preceding characters, or context, into account. The context sorting algorithm sorts a set of all the previous contexts to find the most similar context to the current one. It then predicts the next symbol by sorting previous symbol-context pairs in an order of context similarity. The codeword for the next symbol represents the rank of the symbol in this sorted sequence. The compression performance is evaluated both analytically and empirically. Although the proposed method operates character by character, with no probability distribution used to make a prediction, it has comparable compression performance to the best known data compression utilities.

A uniquely decodable code pair (C, S) is considered for the two-user binary adder channel. When the first code C is linear, a lower bound of |S| is formulated and a uniquely decodable code pair (C, S) is presented. When a rate R₁ of C is less than 1/3, a rate R₂of S is greater than the best rate known previously.

It is well known that the Hopfield Model (HM) for neural networks to solve the TSP suffers from three major drawbacks: (D1) it can converge to non-optimal local minimum solutions; (D2) it can also converge to non-feasible solutions; (D3) results are very sensitive to the careful tuning of its parameters. A number of methods have been proposed to overcome (D1) well. In contrast, work on (D2) and (D3) has not been sufficient; techniques have not been generalized to larger classes of optimization problems with constraint including the TSP. We first construct Extended HMs (E-HMs) that overcome both (D2) and (D3). The extension of the E-HM lies in the addition of a synapse dynamical system cooperated with the corrent HM unit dynamical system. It is this synapse dynamical system that makes the TSP constraint hold at any final states for whatever choices of the HM parameters and an initial state. We then generalize the E-HM further into a network that can solve a larger class of continuous optimization problems with a constraint equation where both of the objective function and the constraint function are non-negative and continuously differentiable.

The mean field theory has been recognized as offering an efficient computational framework in solving discrete optimization problems by neural networks. This paper gives a formulation based on the information geometry to the mean field theory, and makes clear from the information-theoretic point of view the meaning of the mean field theory as a method of approximating a given probability distribution. The geometrical interpretation of the phase transition observed in the mean field annealing is shown on the basis of this formulation. The discussion of the standard mean field theory is extended to introduce a more general computational framework, which we call the generalized mean field theory.

This paper proposes a design technique for 3-D non-separable QMF banks with Face-Centered Cubic Sampling (FCCS) and Body-Centered Cubic Sampling (BCCS). In the proposed technique, 2-D McClellan transformation is applied to a suitably designed 2-D prototype QMF to obtain 3-D QMFs. The design examples given in this paper demonstrate advantages of the proposed method.

This letter propose a fast frequency domain adaptive filter algorithm (FADF) for applications in which large order adaptive filters are required. Proposed FADF algorithm reduces the block delay of conventional FADF algorithms allowing a more efficient selection of the fast Fourier Transform (FFT) size. Proposed FADF algorithm also provides faster convergence rates than conventional FBAF algorithms by using a near-optimum convergence factor derived by using the FFT. Computer simulations using white and colored signals are given to show the desirable features of proposed scheme.

This study is aimed to derive a new theoretical solution for blind equalizers. Undr the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i.e. the tap coefficients of the equalizer appear as an eigenvector of a higher order statistics matrix. Computer simulations show that very fast convergence can be achieved based on the approach.