This paper describes a low-noise and low-power spike neural signal amplifier design that has cutoff frequency compensation between the channels and chips variations. The variation of the frequency characteristics of amplifiers should be minimized among the channels and chips. That is a requirement to do the statistical correlation analysis from a neuroscience point of view. Our design includes the adjustable cutoff frequency using 4 bit variable capacitance. After the compensation the variation of the cutoff frequency was reduced to -0.4kHz to +0.3kHz from -1.1kHz to +3.6kHz that is the value of before trimming under the condition of the target cutoff frequency is 10kHz. We designed a multi neural signal amplifier using ROHM 0.18µm CMOS process. The designed neural amplifier has the capacitive coupled differential input to reject large dc offsets generated at the electrode-tissue interface and to avoid the large common mode noise. To achieve the high energy efficiency with low noise to observe the few tens of µV order spike signal, the MOS transistors in OTA are operated at subthreshold region and combined with low pass filter that consumes less than a hundred nW. The amplifier yielded a midband gain of 37.9dB and the input-referred noise was measured to be 3.76µVrms while consuming 4.30µW with a ±0.9V power supply. These results corresponding to Noise Efficiency Factor (NEF)=2.23 that are close to the value of the limit using a single differential OTA by CMOS process.
This paper describes an analysis of the close to carrier phase noise characteristics of the Colpitts and Butler oscillator circuits. It is shown that the quality factor can be improved by introducing two or more crystal resonators in the oscillation circuits. Based on the Leeson's model, the near carrier phase noise is estimated using the calculated quality-factor obtained by the analysis of the frequency slope in the output impedance. As a result, it was shown by using plural crystal resonators in the phase noise close to carrier frequencies are improved.
Peak SQNR is theoretically calculated for stochastic flash AD converters (SFADC) composed of n comparators with uniformly distributed threshold voltages. A systematic estimation method is presented to obtain minimum required number of comparators for realizing specified SFADC resolution by using comparators with uniformly distributed threshold voltages. Proposed method has been supported by numerical simulations.
This paper proposes a novel output voltage control method for a charge pump. The proposed method uses duty ratio of a clock signal to control the output voltage of a charge pump. Theoretical analysis of the relation between the duty ratio and the output voltage is performed. The proposed method is applied to a charge pump using 2-step charging technique. A determination procedure of a set of duty ratios which realizes the desired output voltage with the maximum power efficiency is explained. Validity of the proposed method is confirmed by HSPICE simulations. The simulation results show that the output voltage of the charge pump is controlled by the proposed method and the output voltage accords with the value estimated by the theoretical analysis. The power efficiency is improved in 7.2% when the output voltage is controlled to 4.5 V.
The Time Analog to Digital Converter (TAD) is a compact, high-resolution A/D converter. TAD uses a Ring Delay Line (RDL). In this paper, we have proposed a method to improve the linearity of TAD using a current-controlled RDL. Simulation showed about 80 percent improvement of linearity compared to the original TAD. Optimum design of proposed circuit and detailed comparison between original TAD and current-controlled TAD are necessary for future work.
In multichannel acoustic echo canceler based on linear combination, the uniqueness problem exists that adaptive filter's can't identify the correct echo-paths due to highly cross-correlated multichannel input signals. Pre-processing for input signal are good candidates for solving this problem. However, it can have the drawbacks to deteriorate audio quality as a secondary problem. In this mis-adjustment problem, the universal solution is not led in the conventional adaptive filter's optimization. In this paper, we propose a new multichannel adaptive echo canceling algorithm based on particle swarm optimization (PSO) without pre-processing to input signals. PSO is a stochastic optimization technique inspired by social behavior of bird frocking or fish schooling, and this is the first attempt to apply it for multichannel acoustic echo cancelers. By performing various simulation we confirm the proposed method can be estimate correct echo-paths with highly cross-correlated input signals.
Scent stimulation is widely used in our daily life such as aromatherapy, however the effect of scent stimulation to humans remains unclear. Therefore, it is necessary to develop a system for evaluation of cardiovascular response to scent stimulation in order to apply it for biofeedback application. In this study, we developed a device for quantitative and short-term stimulation while we evaluated response of heartbeat by scent stimulation with the device. Then, experiments revealed that R-R interval (RRI) was reduced by scent stimulation of grapefruit. In addition, RRI was likely to be controlled by scent stimulations of grapefruit and lavender.
We have proposed a new effective and safe method for the arousal of car drivers using the alternating distributed static magnetic filed stimulation on their spine since 2010, the effectiveness of which has been evaluated for about fifty subjects with the defined arousal index (α+β)/(θ+δ) in the electroencephalogram (EEG) measurements with driver's face monitoring after operation of the driving simulator. We found a remarkable arousal was evaluated at the back-head EEG. Thus we tried to clarify probable mechanisms of the arousal effect of the magnetic stimulation detecting the back magneto-cardiogram using the pico-Tesla resolution amorphous wire magneto-impedance sensor. We obtained a possibility of the arousal based on the probable promotion of the blood flow with the activated blood circulation system.
In recent years, Japanese forests are necessary thinning of the forest. However, the sustainable wood left around there because of expending tremendous effort and costs for carrying woods out. The cut woods have been left around there. This study designs a high maneuverability vehicle with a balance control of a load-carrying platform. The vehicle transport the sustainable woods on the steep sloping ground. This study detected a delay time in regard of controlling the motion of the load-carrying platform. Generalized Minimum Variance Control, one of the predictive control is applied to the controlling system.
To facilitate optimal skill acquisition process, modeling and estimation of individual learning processes will be of key importance. We have proposed a model of skill acquisition based on control theory which enable us to model individual learning process with three parameters; system gain K, time constant T, and dead time L. We measured individual performance time of fault finding task on software programming and successfully obtained the three parameters. These results indicate the feasibility of online estimation of individual learning parameters.
Recently, magnetic thin film devices using magneto resistance (MR) effect are useful for the hard disk drive heads and the magnetic sensors. Therefore magneto resistance effect films have been widely studied, and a rapid progress is being made in this field. We had proposed a new thin-film device. The new proposed thin film device is a magnetic thin film power sensor. The output signal of magnetic thin film power sensor is a dc voltage. In this paper, we report high frequency electric power measurement in the range of MHz frequency with magnetic thin film power sensor.
This paper addresses wind power prediction which is known to be a key technology in EMS(Energy Management Systems). In this paper, 24 hours ahead power prediction method using a filtering theory is proposed for wind power generation. The prediction method is a simple algorithm, the procedure of prediction consists of two steps, the data processing and the calculation of predicted values. In the data processing, in order to get the correlative data from the database, we employ JIT(Just-In-Time) Modeling. In the calculation of predicted value, we propose the regression model for wind speed and wind power, and the unknown parameters are estimated via constrained kalman filter. Moreover, in a procedure of estimation of the unknown parameters, reduction and the convergence of them are also guaranteed. Finally, the advantages of the proposed method over the conventional method are shown through actual prediction evaluations.
A modeling approach of human actions is focused, which designs human action model based on the obtained stored data during long-term monitoring of a person. This approach consists of the following two processes. At first, several kinds of frequent partial time series data are extracted from the stored data and regarded as human action patterns. Next, the extracted time series data are modeled based on a statistical modeling method such as Hidden Markov Model. In this research, it is focused on the extraction method of the frequent time series data in the stored data. A person changes his action according to the change of the situation around him. And, it takes some time for him to perform his action after he recognizes the situation around himself. This time is called delay time in this paper. A human action model considering this delay time leads to greater accuracy in recognition and prediction of human action based on the one. It is necessary to extract time series data of situation and action containing the delay time as learning data in order to generate the above human action model. In conventional methods, multi-dimensional time series data are used as the stored data without distinction between situation and action data. And, some frequent partial time series data are extracted from the stored data. Therefore, the delay time is not considered. In this paper, we propose a new extraction method of a frequent time series data considering the delay time. In this method, the frequent partial time series data with the delay time are extracted by evaluating the repeatability and relativity between the partial time series data with different occurrence time. In the experiment, extraction of a frequent interaction motion between two examinees is executed. The usefulness of the propose method is examined through some experimental results.
This study proposes the model predictive control (MPC) with proportional-integral (PI) controller for coordination of active front steering (AFS) and direct yaw moment control (DYC) maneuvers for path following control in an unmanned ground vehicle system. A single-track mode of lateral-yaw motions based on a linearized vehicle model with linear tire characteristics is used for controller design, while the vehicle model used includes roll dynamic motion for the double-track model with a nonlinear tire model. Based on a known trajectory, we tested the vehicle at high forward speed due the fact that the roll dynamic motion will be influenced at high vehicle speed for a double lane change scenario in order to follow the desired trajectory as close as possible, while rejecting the effects of a wind gust. We compared two different controllers; i) MPC with PI of an AFS and, ii) MPC with PI for coordination of AFS and DYC. The simulation results show the proposed coordinated control yielded better tracking performance through high speed maneuvers than AFS maneuvers only. It also demonstrates that the proposed control methods are useful to maintain and enhance vehicle stability along the desired path, and has the ability to eliminate the effect of crosswind.
Plasma measuring methods have been developed to measure the properties of plasmas which cannot be touched directly. For instance, Quadropole Mass Spectroscopy (QMS) was developed to survey what kinds of compound are included in the plasma directly. We have measured by using Plasma Emission Spectroscopy method. It has been considered to be one of the effective method because of not affecting the plasma. We have developed a new type of plasma spectroscopic device by an image processing method. On this paper, we'd like to report advantages and differences between the new device and the old one.
In the present paper, we propose a method that can acquire cooperative action to reach an appropriate goal without controlling reward by designers. To accomplish this, we introduce a new concept of reward interpretation. It is an idea that an agent can increase or decrease reward given by an environment through the reward interpretation by itself. We applies this idea to a Q-learning method. The simulation results show that the proposed method is superior to a standard Q-learning method and a Q-learning method with cooperation in terms of the number of successful cooperation.
The number of lines of code in the embedded software has been growing. In the reuse-based embedded software development, it is increasing of cases that accumulate software from two or more products. It has become inevitable to reuse the existing software. However, if the existing software to be reused is not well managed or organized, nobody will be able to know which modules would be affected when some parts of the reused software are modified. In this paper, we propose a method to accomplish the effective reuse of software modules by managing dependency information among modules and having development management property data to each module. We have developed a configuration management tool that visualizes mutual relations among existing software modules and visually presents not only dependency among modules but also development management property data of modules according to the developer's demand for reuse of modules. We evaluated the method by applying it to some actual developments.
Event-related potential (ERP) was measured when pictures of shirts with five different colors, and with characters of five different fonts, were subjectively evaluated by three opinions; ‘1st preference’, ‘2nd preference’ and ‘Others’. In result, P300 amplitude for the opinion ‘1st preference’ is larger, which indicates a potential to distinguish the subjective preference on the design evaluation by ERP.
In this paper an active noise control system using single adaptive filter is proposed. The cost function of this adaptive system is a square sum of the cross-correlation coefficient of the input noise and the output error signal. The adaptive algorithm of this single adaptive filter is formulated and the convergence performance is verified by computer simulation.
This paper proposes the Japanese flag signaling recognition method based on self-organizing maps, and describes its evaluation result. Kinect, which is one of the consumer sensor device and was used in the previous studies of Ahmed et al. and Ishikawa, was adopted as the input device in this study. The proposed method is able to recognize the Japanese flag signaling with higher recognition rate than that of the previous studies in which Kinect was used.