In this article, a new type of diffusion template and an analogic CNN algorithm using this diffusion template for detecting some lung cancer symptoms in X-ray films are proposed. The performance of the diffusion template is investigated and our CNN algorithm is verified to detect some key lung cancer symptoms, successfully.

Modern database systems have to support complex data objects, which appear in advanced data models such as object-oriented data models and nested relational data models. Set-valued objects are basic constructs to build complex structures in those models. Therefore, efficient processing of set-valued object retrieval (simply, set retrieval) is an important feature required of advanced database systems. Our previous work proposed a basic scheme to apply superimposed coded signature files to set retrieval and showed its potential advantages over the B-tree index based approach using a performance analysis model. Retrieval with signature files is always accompanied by mismatches called false drops, and proper control of the false drops is indispensable in the signature file design. This study intensively analyzes the false drops in set retrieval with signature files. First, schemes to use signature files are presented to process set retrieval involving "has-subset," "is-subset," "has-intersection," and "is-equal" predicates, and generic formulas estimating the false drops are derived. Then, three sets of concrete formulas are derived in three ways to estimate the false drops in the four types of set retrieval. Finally, their estimates are validated with computer simulations, and advantages and disadvantages of each set of the false drop estimation formulas are discussed. The analysis shows that proper choice of estimation formulas gives quite accurate estimates of the false drops in set retrieval with signature files.

Our compact switching converter using a thin-film microtransformer mono-lithically integrated with rectifier diodes represents the first step in developing a monolithic micro-switching converter that can be integrated with semiconductor devices and magnetic components. This converter is a single-ended forward converter with resonant reset and operates successfully at 15 MHz. The maximum output power is 0.5 W.

In this letter, we obtain the absolute exponential stability result of neural networks with globally Lipschitz continuous, increasing and bounded activation functions under a sufficient condition which can unify some relevant sufficient ones for absolute stability in the literature. The obtained absolute exponential stability result generalizes the existing ones about absolute stability of neural networks. Moreover, it is demonstrated, by a mathematically rigorous proof, that the network time constant is inversely proportional to the global exponential convergence rate of the network trajectories to the unique equilibrium. A numerical simulation example is also presented to illustrate the analysis results.

In this paper, the error performance of block coded 8-PSK modulation systems of length 32, designed for unequal error protection (UEP) of messages transmitted over a Rayleigh fading channel, is investigated. Computer simulation are reported showing that, with transmission over a Rayleigh fading channel, a good improvement in coding gain is obtained by the use of a binary linear UEP (LUEP) code as a constituent code in the multilevel construction, compared with conventional block coded modulation (BCM) of the same length.

Electric fishes generate an AC electric field around themselves by the electric organ in the tail. Spatial distortion of the field by nearby objects is detected by an electroreceptor array located an over the body surface to localize the object electrically when other senses such as vision and mechanosense are useless. Each fish has its own 'frequency band' for its electric organ discharges, and jamming of the electrolocation system occurs when two fish with similar discharge frequencies encounter. To avoid janmming, the fish shift their discharge frequencies in appropriate directions. A computational algorithm for this electrical behavior and its neuronal implementation by the brain have been discovered. The design features of the system, however, are rather complex for this simple behavior and cannot be readily explained by functional optimization processes during evolution. To gain insights into the origin of the design features, two independently evolved electric fish species which perform the same behavior are compared. Complex features of the neuronal computation may be explained by the evolutionary history of neuronal elements.

This paper describes novel techniques for analyzing power MOSFETs. Since the gate width of power MOSFETs is much larger than that of power MESFETs or HJFETs, an appropriate device design to suppress matching circuit losses is needed. These losses and the intrinsic device characteristics are analyzed employing the proposed techniques, which are based on large-signal simulations. Also, new formulas describing the dependence of saturated output power on gate width are derived to perform loss-minimized design. These techniques are applied to the design of power MOSFETs for GSM cellular telephones. As a result, an output power of 35.5 dBm with a power-added efficiency of 55% and a power gain of 10.5 dB at 900 MHz have been achieved.

A clock-feedthrough (CFT) compensation technique using a dummy cell is valid when the CFT current from a switched-current (SI) memory cell is signal-independent. Based on this idea, a SI dummy cell appropriate for the S2I cell is developed. Simulations show that the CFT rejection ratio as high as 60dB is attainable over the temperature range from -30 to 80 with this architecture. The CFT-compensated SI cell proposed here is, therefore, quite usuful for high-accuracy, current-mode signal processing.

Given the recent advances in telecommunication services, new service operations are needed that support not only existing network services, but also information and communication providing services, such as multimedia services. It is particularly important that service usage information should be gathered, processed, analyzed and presented properly for smooth service provisioning and business support. This paper defines a reference model for service usage information and an implementation model for establishing the functions needed to gather and process this information. The results of an service operation system as implemented in NTT multimedia service trials, currently underway in the city of Urayasu, are also described.

The technique of common-multiplicand multiplication, CMM, is modified and the similar approach is utilized to enhance the performance of a recently proposed fast exponentiation algorithm by exponent decomposition. On average, the improved exponentiation, its original version, and the traditional right to left binary exponentiation algorithm take 1.292m+11,1.375m+3, and 1.5m multiplications, respectively where m is the bit length of the exponent. Finally, it is shown how to improve the overall performance of an exponentiation by employing the improved exponentiation algorithm, the improved CMM algorithm , and any general purpose fast multiplication algorithm.

A pipelined adaptive digital filter (ADF) architecture based on a two-dimensional least mean square algorithm is proposed. This architecture enables the ADF to be operated at a high clock rate and reduction of the required amount of hardware. To achieve this reduction we introduce a new building unit, called a block, and propose implementing the pipelined ADF using the block, Since the number of blocks in a cell is adjustable, we derive a condition for satisfying given specifications. We show the smallest number of blocks and the corresponding delay can be determined by using the proposed method.

We discuss a new decoder for the multiple-valued signed-digit number, using a current-mode CMOS transistor-oriented circuit structure. In this paper, a new decoding method with the selective summation of a redundantly represented addend "O = [-1 r]" is proposed, where r is the radix and the addend is applied to each digit with a negative value and any consecutively higher digit takes which has a value of O. A newly designed literal linear circuit is realized, which has a current-switch function that makes independently the short path when each digit has a value of O. Through the parallel connections of these current swiches, the same addend signal at the lower digit is transmitted in a higher speed, The decoder circuit is tested by using the general circuit simulation software SPICE and the circuit characteristics of the selective summation of a redundantly represented O addend and the output results of the SD decoding operation were simulated. We also evaluated the decoder circuit in terms of the processing speed and the circuit size.

This paper proposes a prediction method for non-stationary time series data with time varying parameters. A modular structured type neural network is newly introduced for the purpose of grasping the changing property of time varying parameters. This modular structured neural network is constructed by the hierarchical combination of each neural network (NNT: Neural Network for Prediction of Time Series Data) and a neural network (NNW: Neural Network for Prediction of Weights). Next, we propose a reasonable method for determination of the length of the local stationary section by using the additive learning ability of neural networks. Finally, the validity and effectiveness of the proposed method are confirmed through simulation and actual experiments.

Analysis of electroencephalogram (EEG) is presented for sleep physiology. This analysis is performed by the Instantaneous Maximum Entropy Method (IMEM), which was given by the author. Appearance and continuation of featuristic waves are not steady in EEG. The characteristics of these waves responding to epoch of sleep are analyzed. The behaviours of waves were clarified by this analysis as follows; (a) time dependent frequency of continuous oscillations of alpha rhythm was observed precisely. Sleep spindles were detected clearly within NREM and these parameters of time, frequency, and peak energy were specified. (b) delta waves with very low frequencies and sleep spindles were observed simultaneously. And (c) the relationship of sleep spindles and delta waves was first detected with negative correlation along time-axis. The analysis by the IMEM was found effective comparing conventional analysis method of FFT, bandpass filter bank, etc.

A neural network approach called the "Gradual Neural Network (GNN)" for the time slot assignment problem in the TDM multicast switching system is presented in this paper. The goal of this NP-complete problem is to find an assignment of packet transmission requests into a minimum number of time slots. A packet can be transmitted from one source to several destinations simultaneously by its replication. A time slot represents a switching configuration of the system with unit time for each packet transmission through an I/O line. The GNN consists of the binary neural network and the gradual expansion scheme. The binary neural network satisfies the constraints imposed on the system by solving the motion equation, whereas the gradual expansion scheme minimizes the number of required time slots by gradually expanding activated neurons. The performance is evaluated through simulations in practical size systems, where the GNN finds far better solutions than the best existing altorithm.

Calculation Nv(x) of complex order v numerically, we must calculate Df{JN+ε(x)}. When Df{JN+ε(x)} is calculated by the recurrence method, this letter will analyze the error of Df{JN+ε(x)}, and will determine the optimum number of recurrences.

Scattering of a plane electromagnetic wave by a conducting wedge will be discussed. The former solution can not be applicable to all the transition regions when its parameter is constant. This study shows a new solution which consists of only one expression applicable to the shadow region, the illuminated region and the transition regions, and which has no parameter.

Event-related are the kind of signals that are time-related to a given event. In this work, we will study the effect of bias and overlapping noise on Fourier linear combiner (FLC)-based filters, and its implication on filtering event-related signals. We found that the bias alters the weights behaviour, and therefore the filter output, and we discuss solutions to the problem of spectral overlap.

In recent years, fractal processes have played important roles in various application fields. Since a 1/f process possesses the statistical self-similarity, it is considered sa a main part of fractal signal modeling. On the other hand, noise reduction is often needed in real-world signal processing. Hence, we propose an enhancement algorithm for 1/f signal disturbed by white noise. The algorithm is based on constrained minimization in a wavelet domain: the power of 1/f signal distortion in the wavelet domain is minimized under a constraint that the power of residual noise in the wavelet domain is smaller than a threshold level. We solve this constrained minimization problem using a Lagrangian equation. We also consider a setting method of the Lagrange multiplier in the proposed algorithm. In addition, we will confirm that the proposed algorithm with this Lagrange multiplier setting method obtains better enhancement results than the conventional algorithm through computer simulations.

Cross talk in mode-division multiplexing system is studied. The mode patterns when the fiber is bent are observed in the experiment.