Since the conventional figure of merit (FOM) neglects the flicker-noise effect in a voltage-controlled oscillator (VCO), we devised a new FOM that considers the flicker-noise effect and, thus, allows phase noise (which is dominated by flicker noise) of different VCOs to be compared. Using the proposed FOM, we analyze the phase noise and power dissipation in an inverter-based ring oscillator, since it has a simple topology and few noise sources. From this analysis, we draw three conclusions: first, varying load capacitance changes oscillation frequency only without changing proposed FOM; second, to improve the proposed FOM, large transistor length should be chosen, third, comparing FOM of a VCO and FOM calculated from target specifications of phase noise and power dissipation shows that the designed VCO meets target specifications. This second and third conclusion is useful for easily designing an actual inverter-based quadrature-ring VCO. A prototype inverter-based quadrature-ring VCO was fabricated by using 0.18-μm CMOS technology with an active die area of 0.018 mm². It consumes 2.61 mW from a 1.8-V power supply. Moreover, it has an oscillation frequency of 338.5 MHz, phase noise of -110 dBc/Hz at 1-MHz offset frequency, and proposed FOM of 160.4 dB (at 0.1-MHz offset frequency).

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Event Related Potential (ERP) of brain EEG (Electroencephalogram) activity plays an important role in EEG phase synchronization and/or hemodynamic responses measured by fMRI (functional Magnetic Resonance Imaging). However, the specific mechanism of ERP generation is still unclear. In this study, pulse and noise type visual stimuli are administered to subjects. Then the phase response of the EEG in α-waves is analyzed. As a result, the magnitudes of the phase response are varied by the stimulus administered phase and no power increase is observed. These results indicate that the ERP in α-waves is generated by the phase resetting of brain activity.

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This paper describes an optimal mapping of the torus self-organizing map for a human forearm motion discrimination on the basis of the myoelectric signals. This study uses the torus self-organizing map (Torus-SOM) for the motion discrimination. The normal SOM identify input data into the same feature group by using the all units of map. Then there is a possibility of the misrecognition motion around the boundary lines of the motion groups. Therefore, this study proposes the mapping method of SOM that the learning units of the same motion concentrate on one local range and the learning unit groups of each motion separates enough. As a result, the variance in the same motion group becomes small and the variance between each motion groups becomes big. Some experiments on the myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.

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To maintain or promote the health condition of elderly citizens is quite important for Japan. Given the circumstances, the Ministry of Health, Labour and Welfare has established the standards for the activities and exercises for promoting the health, and quantitatively determined the exercise intensity on 107 items of activities. This exercise intensity, however, requires recording the type and the duration of the activity to be calculated. In this paper, the exercise intensities are estimated using 3D accelerometer for 25 daily activities. As the result, the exercise intensities were estimated to be within the root mean square error of 0.83 METs for all 25 activities.

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Response surface method based on multivariate analysis models is applied to search manufacturing conditions which improve conversion efficiency of Fuji Electric's newly developed thin film solar cells in its trial manufacturing. Difficulties in this problem include: 1. The manufacturing process has many condition parameters to determine, and design of experiments (DoE) is difficult to apply, 2. Obtained data contains lots of noise caused by fluctuation of properties in manufacturing apparatus under same condition settings. Sets of new methodologies have been developed to cope with these difficulties as follow: 1. Data pretreatment suitable for solar cell manufacturing process, 2. Response surface method using partial least squares with nonlinear term, 3. Optimization method searching within interpolation in multivariate search space and with correlations of variables kept.

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Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

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This paper proposes a cooking amount estimation method for rice cookers based on Mahalanobis-Taguchi system. This estimation is important in that it can improve the cooking quality significantly. The proposed method enables us to estimate the amount in the early stage of cooking, thereby to give optimal heat in the whole process. To this end, an existing method adopts the minimal cooking quantity as a standard quantity and conduct estimation via outliers in terms of Mahalanobis distance, but this is easily affected by consumers' usage and nonlinearity peculiar to heat systems. Estimation precision is expected to be higher if the estimation is used by correlation of each characteristic data. The proposed method achieves this by adding sign to the estimation method for treating negative values in Mahalanobis distance, and verifies its effectiveness by experiments.

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Carrier type dynamic strain amplifiers are frequently used for stress measurement with strain gages. That is because the carrier type dynamic strain amplifier can conduct high precision measurement since it is highly resistant to external noise or power noise in the field. The strain gage has little effect on specimen being measured since it is small and light weight. However it is required to connect the input cable from the target strain gage to the amplifier. In case of using the carrier type dynamic amplifier, distributed capacitance due to the input cable greatly effects zero point variation.
The distributed capacitance changing degrades the stability of the dynamic strain amplifier.
We made up and logically clarify Dual Feedback CST (Capacitance Self Tracing) method that detects, self-tracks and eliminates the capacitive component generated in any arm of the measuring bridge. The zero-point variation is not affected by the carrier frequency and resistance value and can be cancelled if the bridge is balanced in the CST method.
We conducted experiments with strain gage resistance 120 ohm or 350 ohm and carrier frequency 5 kHz, 12 kHz or 28 kHz and verified the zero-point stability.

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Auditory information plays an integral role in AV media because even identical images are perceived differently when they are matched with different music. However, we now present a few studies in which the changes in subjective perceptions were analyzed on the basis of the physical properties of the perceived items. The purpose of this study is to investigate the effects of music on image impression in terms of the physical properties of images. In this paper, we first elucidate the changes in subjective impressions when the image is presented by itself and when it is presented with music. Secondly, to clarify the relation between the impression of an image or music and physical properties, we compare the different image or music perceptions with each other and also compare their respective physical properties, which include color information, structural information, and frequency characteristics. As a result, the color information of an image containing green or saturation colors and the power of the music were strongly correlated with adjectives expressing activity. Moreover, the entropy of saturation correlated with words expressing spatial extent.

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Document classification is one of important topics in the field of NLP (Natural Language Processing). In the previous research a document classification method has been proposed which minimizes an error rate with reference to a Bayes criterion. But when the number of documents in training data is small, the accuracy of the previous method is low. So in this research we use estimating data in order to estimate prior distributions. When the training data is small the accuracy using estimating data is higher than the accuracy of the previous method. But when the training data is big the accuracy using estimating data is lower than the accuracy of the previous method. So in this research we also propose another technique whose accuracy is higher than the accuracy of the previous method when the training data is small, and is almost the same as the accuracy of the previous method when the training data is big.

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This study proposes a robust cooperated control method combining reinforcement learning with robust control to control the system. A remarkable characteristic of the reinforcement learning is that it doesn't require model formula, however, it doesn't guarantee the stability of the system. On the other hand, robust control system guarantees stability and robustness, however, it requires model formula. We employ both the actor-critic method which is a kind of reinforcement learning with minimal amount of computation to control continuous valued actions and the traditional robust control, that is, H_∞ control. The proposed system was compared method with the conventional control method, that is, the actor-critic only used, through the computer simulation of controlling the angle and the position of a crane system, and the simulation result showed the effectiveness of the proposed method.

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The interconnected recurrent neural networks are well-known with their abilities of associative memory of characteristic patterns. For example, the traditional Hopfield network (HN) can recall stored pattern stably, meanwhile, Aihara's chaotic neural network (CNN) is able to realize dynamical recollection of a sequence of patterns. In this paper, we propose to use meta-heuristic (MH) methods such as the particle swarm optimization (PSO) and the genetic algorithm (GA) to improve traditional associative memory systems. Using PSO or GA, for CNN, optimal parameters are found to accelerate the recollection process and raise the rate of successful recollection, and for HN, optimized bias current is calculated to improve the network with dynamical association of a series of patterns. Simulation results of binary pattern association showed effectiveness of the proposed methods.

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A delivery route optimization that improves the efficiency of real time delivery or a distribution network requires solving several tens to hundreds but less than 2 thousands cities Traveling Salesman Problems (TSP) within interactive response time (less than about 3 second), with expert-level accuracy (less than about 3% of error rate). Further, to make things more difficult, the optimization is subjects to special requirements or preferences of each various delivery sites, persons, or societies. To meet these requirements, an Inner Random Restart Genetic Algorithm (Irr-GA) is proposed and developed. This method combines meta-heuristics such as random restart and GA having different types of simple heuristics. Such simple heuristics are 2-opt and NI (Nearest Insertion) methods, each applied for gene operations. The proposed method is hierarchical structured, integrating meta-heuristics and heuristics both of which are multiple but simple. This method is elaborated so that field experts as well as field engineers can easily understand to make the solution or method easily customized and extended according to customers' needs or taste. Comparison based on the experimental results and consideration proved that the method meets the above requirements more than other methods judging from not only optimality but also simplicity, flexibility, and expandability in order for this method to be practically used.

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The circulation bills include a large amount of fatigue bills which cause various types of problems such as the paper jam in automatic tellers due to overworked and exhausted bills. The high accuracy bill classification technique, which identifies the level of fatigue in the bills as well as distinguishes between the used and the new ones, is greatly required in order to prune these fatigued bills. The purpose of this paper is to propose a classification method of fatigue bills based on acoustic signals. The amplitude difference in the acoustic signal of bills is employed as characteristics of the bill classification. Further, a Support Vector Machine (SVM) is introduced as a classification method. We then perform the classification experiments using the acoustic signals from the practical bill conveyance device in order to show the effectiveness of the proposed method by the bill identification experimentation.

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Toward facile introduction of metadata-based document management system, we propose an algorithm which uses sample documents and their manually specified metadata as training data, and generates metadata-extraction rules. Our algorithm enumerates candidates of keywords and layout characteristics specific to the metadata on the basis of metadata occurrence in the training data. And then it examines whether each candidate is specific to only one kind of metadata. In an experiment on Japanese business documents and weekly reports, automatically generated rules have achieved metadata extraction as accurate as manually adjusted one.

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In order to obtain MMIC of a feed circuit called a HTBM (Hybrid Three Direction Beam Matrix) for making compact phased array antennas, the HTBM that uses LC circuitry as substitute for its transmission line was designed, experimentally fabricated and then evaluated at 1 MHz. In addition, a switch circuit for switching a beam direction was made using FETs and built into the HTBM. Antenna output was evaluated. Its results showed that the output gave close agreement with its simulation value and that the antenna-to-antenna phase difference and the level difference were less more than 7 degrees and 3.3 dB, respectively, in comparison with its ideal value.

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All optical signal sampling technique using a high nonlinear fiber is experimentally investigated in order to observing a waveform of a high symbol-rate optical signal. Optical sampling pulses having time width of 2.8 ps are generated from an output of a semiconductor mode lock laser module by reducing the pulses using optical gates. Envelope of the optical signal is sliced to the slow rate signal by the sampling pulses through the effect of four wave mixing caused in the high nonlinear fiber. Applying this manner, simple and less alignment system is realized. In order to confirm the basic operation of the scheme, signal conversion efficiencies to idler light are evaluated by using two types of fiber. Moreover, optical signal sampling experiments are carried out by using a 160 Gb/s On-Off-Keying signal.

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This letter classifies snoring sounds into three breathing routes (oral, nasal, and oronasal) with discriminant analysis of the power spectra and k-nearest neighbor method. It is necessary to recognize breathing route during snoring, because oral snoring is a typical symptom of sleep apnea but we cannot know our own breathing and snoring condition during sleep. As a result, about 98.8% classification rate is obtained by using leave-one-out test for performance evaluation.

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