マイクロ波・ミリ波を含む広い周波数帯の電磁波の応用分野は，情報通信のみならず，工業，化学，エネルギー，医療，セキュリティなどその応用範囲は拡大し続けている。特に，近年においては，人に限らずあらゆる物をネットワークに接続するIoT（Internet of Things）が普及し，セン

We have proposed a small antenna designed to radiate directly from AMC (AMC antenna). In this paper, the calculated results of two-dimensional distribution of the mutual coupling and the correlation coefficient are discussed by the AMC antenna and a planar inverted-F antenna (PIFA). Especially, the mutual coupling and the correlation coefficient of AMC antenna are measured.

In this paper, an experimental study on a lumped-element-type power divider consisting of an extremely small number of circuit elements is conducted in SHF band. The authors have already reported theoretical and experimental studies on power dividers utilizing a chip element as a lumped element. However, the self-resonant frequency of the chip element is expected to adversely affect the circuit characteristics in the frequency band such as the SHF band. And its effectiveness has been confirmed by electromagnetic simulations and trial experiments.

Recently, a wireless communication system called LoRa has been adopted for various IoT devices. We are studying the way to change communication parameters according to the radio wave usage. In that research, a method to detect the radio wave usage status of LoRa signal in each SF is developed, even if multiple SFs are mixed in one channel. Furthermore, the method is implemented in the equipment named “LoRa Finder.” In this paper, we describe the detection method in detail and explain the hardware and software of the equipment to realize it.

The era of Internet of Things (IoT) utilizing a large number of wireless sensors is approaching. Such microwave and millimeter wave IoT devices are required not only to have high performance and reliability, but also to have a low cost, variety products and quick developments. Realization of the planer type circuits with an FDM type 3D printer is one of a solution to meet these requirements. In the FDM type, the internal structure of the printed product can be changed easily by printer settings. That mean the complex permittivity of a 3D printed substrate will be able to controlled arbitrarily by RF designer. In this paper, the printing conditions and the complex permittivity of a thin thermoplastic ABS resin substrate for the FDM type 3D printer are studied using the TE₀₁₁ mode cylindrical cavity resonator method in the 36 GHz band. It is clarified that the relative deviation of the complex permittivity is about 1.5%, and the effective complex permittivity is decreased by the surface unevenness caused by the FDM method. We expect the results can be useful to develop low cost and rapid realization of wireless devices with AM technology for next generation sustainable society.

As seen in IoT (Internet of Things) and 5G (fifth generation mobile communication), digital wireless communication technology is now essential to our lives. In this technical note, our goal is that we provide an outline and a trend for multi-antenna systems from the viewpoint of signal processing toward beyond-5G and 6G. First, the outline and connections of the multi-antenna system such as reception, transmission diversity and MIMO (Multi Input Multi Output), which is essential for high reliability and speed wireless communication, are summarized. Next, we introduce our research results on STBC-CPM (Space Time Block Coded - Continuous Phase Modulation) MIMO system for the sky IoT and OAM (Orbital Angular Momentum) transmission.

The authors propose a novel space filter that combines a periodically perforated metal plate and the dielectric layers. In this study, we confirmed that these structures function as electromagnetic wave transmission control materials by FDTD analysis and experiments in free space.

IoT is attracting attention as a means of solving problems for realizing a sustainable society. To realize IoT, edge computing is required in addition to clouds and networks. The authors developed a technology to detect the closing of injectors and pumps by signal processing of the drive current. The concept of detecting the inductance change due to the actuator motion used here by signal processing has also been studied for latch solenoid valves and SR motors. It can be concluded that the solenoid valve motion detection technology has universality as a basic technology for IoT.

We aim to realize combined motions of a robotic hand such as a myoelectric prosthetic arm by using Electromyography (EMG) of surface and deep muscles. A hybrid motion estimator is proposed to recognize hand motions corresponding to measured EMG and to estimate the joint angles during each hand motion. The hybrid motion estimator consists of Back-Propagation Neural Network (BPNN) and Multi-Input Single-Output (MISO) Nonlinear ARX (NARX) model. The hybrid motion estimator improve the estimation accuracy by considering a state transition from a previous state of hand motion to current one. The hybrid motion estimator has allowed to recognize both single motions, transition during single motions and a part of combined motions, and to estimate the corresponding joint angles with high accuracy. After verifying the effectiveness of the proposed estimator through numerical simulations, we have demonstrated that a robotic hand follows the estimated joint angles during recognized hand motion from measured surface and deep EMG of subjects.

In this paper, we propose a method for designing a low-delay integer-order differentiators based on maximally flat in the passband and equiripple criteria in the stopband. The proposed function consists of two functions. One of the functions has low-delay and flat characteristics in both the passband and the stopband. The other function is designed so that the whole function has an equiripple characteristic in the stopband. The low-delay low-pass/band-pass integer-order differentiators designed by the proposed method realize highly accurate differential estimation near the desired frequency and sharp cutoff characteristics.

This paper clarifies variability of behavior of Phase-Only Correlation functions under frequency transformation of continuous-time signals. The signals are classified into two categories: continuous time signals defined on a continuous time axis and discrete time signals defined on a discrete time axis. Continuous time signals are converted into discrete time signals by sampling at arbitrary periods when signal processing is performed. When a discrete-time signal is obtained by sampling a continuous-time signal with a constant sampling period, the phase defined by (-∞, ∞) in the continuous-time signal is restricted to (-π, π] in the discrete-time signal. It is necessary to consider the nature of the POC functions for continuous-time signals, which has been analyzed for discrete- time signals in previous studies.

In order to preserve the information in the phase spectrum at continuous time, it is necessary to suppress the changes in the phase spectrum that occur during the sampling of the signal. In this paper, we propose a nonlinear transformation of the phase spectrum using the projection method in continuous time.

We propose an efficient framework with compatibility between normal printing and printing with special color inks in this paper. Special color inks can be used for printing to represent some particular colors and specific optical properties, which are difficult to express using only CMYK inks. Special color layers are required in addition to the general color layer for printing with special color inks. We introduce a reversible data hiding (RDH) method to embed the special color layers into the general color layer without visible artifacts. The proposed method can realize both normal printing and printing with special color inks by using a single layer. Our experimental results show that the quality of the marked image is virtually identical to that of the original image, i.e., the general color layer.

We propose an efficient framework of reversible data hiding to preserve compatibility between normal printing and printing with a special color ink by using a single common image. The special color layer is converted to a binary image by digital halftoning and losslessly compressed using JBIG2. Then, the compressed information of the binarized special color layer is reversibly embedded into the general color layer without significant distortion. Our experimental results show the availability of the proposed method in terms of the marked image quality.

A lot of multiplication circuits and a large-scale memory are required to operate a neural network. However, it is also necessary to use a low-power consumption and small-scale processor with a neural network for an embedded image-processing system. A binarized neural network (BNN) operating on the basis of the binary operation method is one of the candidates for solving such problems because the multiplication circuit is unnecessary, and a relatively small memory is required. In this study, an ultrasmall processor was designed with a specialized BNN based on the processor with a very small area for function, “Pilaf.” The processor designed is called “Pulin,” in which a control circuit is added that can access a large memory area and an image-processing arithmetic circuit. Despite the addition of some circuits, the design of Pulin demonstrates the same chip area as that of Pilaf because the architecture and the state machine are optimized. In addition, the processing time taken in the case of the neural network execution was reduced to approximately half that of the conventional processor. In addition, a large-scale integration (LSI) circuit was fabricated, and the delay time and operation speed of Pulin were analyzed using an LSI tester.

To realize fast distribution control on edge controllers, we have proposed formula manipulation based fast distribution control method. We have shown that the method can calculate optimal solutions for load distribution problems, and extended the method by tabulation and introducing weighting factors. In this paper, we extended the method to predictive control problems for multi-input multi-output(MIMO) systems. The new proposed method can calculate optimal input values to match output values with predictive reference values. The calculated input values satisfy constraint conditions, including rate of change constraints. We applied the proposed method to an example of refrigeration cycle model, and evaluated performance comparing with PID control.

A key point of reducing injury rates for first responders is spending less time to reach a target in a dangerous area. First responders and rescue robots are applied in previous researches using dangerous areas search and obstacle avoidance. Unmanned aerial vehicles (UAVs) are also started to use for disaster management. Therefore, path planning for the first responders and rescue robots are needed the during dangerous area searching using UAVs. Here, path planning algorithms for the first responders and rescue robots are needed to global path planning and it is better to use different kinds of node-based algorithms depending on a known and a partially known environment. An A* algorithm is suitable in the known environment and a D* lite algorithm is proper in the partially known environment. However, long path calculation time is always an issue of the node-based global path planning. For the long path calculation time, a novel diagonal path planning algorithm is proposed in this paper. The main idea of the diagonal path planning is to use diagonal nodes instead of surrounded nodes from current node selection steps. Also, it causes a zig-zag path issue, so a path smoothing with a bounded curvature is proposed to solve the zig-zag issue. The effectiveness of the proposed algorithm is confirmed through simulations.

We have proposed a modeling method of human actions based on the causality between a situation and an action. In this method, a human action rule is expressed by an If-the-rule style, assumed that a person changes his current action to the next one according to the situation around him. In the previous method, a human action and a situation in a human action rule is modeled with a Hidden Markov Model(HMM). HMM is one of powerful tools for modeling time series data, but it ignores the change speed of time series data. In addition, time series data on human actions and situations are classified by Continuous Dynamic Programming. This means that two types of criteria should be set for modeling. In order to overcome these problems, we propose a new modeling method of human actions with Hidden Semi-Markov Model(HSMM) in this paper. In the proposed method, both clustering and modeling of time series data are executed with HSMM. The usefulness of the proposed method is discussed through some modeling results of human actions on operating a radio-controlled vehicle.

This paper presents a synthetic data generation method using a robot to create a substantial dataset. One important task in the field of learning-based recognition is to collect large amounts of high-quality training data. To increase the training dataset, many researches have used data augmentation methods. In musical recognition, data augmentation is implemented using digital signal processing methods including pitch-shifting and time-stretching. Data augmentation is a limited method because it depends on prior knowledge of the data and it cannot be performed all domains. We propose a new dataset collection method using a robot that automatically plays musical instruments, which enables high-quality data to be added to the training samples. We compare the results with two kinds of human dataset and a mixed dataset, which include human and robot datasets, using four kinds of convolutional neural networks (CNNs). The results indicate that the proposed method using CNNs analyzing the mixed dataset with a guitar-playing robot, can outperform CNNs using the human dataset.

Many people can distinguish whether the meat is grilled or not by the color of the meat. People with dichromacy, however, are hard to do this. Such characteristic in which the color seen by a human looks different is called color vision diversity. In this paper, we propose a smartphone application for color vision diversity in which we can easily judge the degree of grilled meat. This application obtains the image of the meat by a camera of the smartphone, and modifies the color of the raw meat. We investigated five methods of the modification. We conducted experiments to evaluate the application. We presented 90 images of grilled or raw meat to 37 subjects by changing the modification method. Each subject answered the meat presented is grilled or not. As a result of the experiments, the method adding blue color to the raw meat and changing raw meat to the yellow-blue lattice pattern are effective to reduce the misjudgement that raw meat is roasted.

We propose a tool position tracking system in a machining facility. It will be able to track tools that are hidden under other objects. We will also research the frequency of processing that gives practical tracking accuracy.

When the tool is hidden or cannot be recognized by the camera, system recognizes that it is in the same position based on past location information and continues tracking.

We checked accuracy based on the degree of match with visual tool tracking. We experimented with the case of one and two workers. The tracking accuracy of this study was higher than track method of only visible tool. In the case of one worker operation, for intervals less than 8 seconds, the tracking accuracy was over 95%. In the case of two workers operation, even at the maximum frequency of the processing, the tracking accuracy was 90%.

The target for tracking accuracy was not met. However, we were able to track tools that are hiding under other objects.

This paper considers a preference optimization problem which requires the best Pareto solution for a decision maker's preference among the Pareto solution set of a multi-objective optimization problem. Even if the decision maker's preference is expressed by formula explicitly, it is difficult to solve the this type of problems, because Pareto solution set as their constraint cannot be described analytically. In our approach, choosing one of Pareto solutions is considered as a map from weighting coefficient parameter in a problem to minimize the maximal component of the multi-objective functions, and the preference optimization problem is transformed into a bi-level optimization problem in which the best weighting coefficient is chosen so as to optimize the decision maker's preference with the minimization problem of maximal component of the multi-objective functions. Then, the map is generated approximately with linear combination of radial basis functions on the weighting coefficient space by using optimization procedure with an active learning method presented by the authors, in which effective weighting coefficient data are generated for searching the Pareto solution with the best preference successively. Results of computer simulation for simple examples show effectiveness of the presented integrated optimization method for preference optimization problem.

Basic research was conducted to establish a visible light-pumping fiber amplifier using solar light for optical telecommunication. First, absorption properties of erbium-doped fiber (EDF) in the visible light wavelength region were investigated. Results show that the absorption coefficient α is large for 521 nm wavelength. Moreover, the emitted light property and the optical signal amplifier property were investigated for a laser diode (LD) to emit in the visible light region. An optical signal amplification gain of 3.87 dB was confirmed. Furthermore, emitted light properties, EDF active lengths, and erbium concentration properties were assessed using a solar lighting system.

By carrying out the present study, it will be possible to help considerably to construct no power supply optical fiber communication systems operable solely using only solar light to develop the optical communication infrastructure for the incomplete area with electric power and information infrastructure or for blackouts caused by disasters.