Junnosuke HOSHIDO Tonan KAMATA Tsutomu ANSAI Ryuhei UEHARA
Shin-ichi NAKANO
Shang LU Kohei HATANO Shuji KIJIMA Eiji TAKIMOTO
Lin ZHOU Yanxiang CAO Qirui WANG Yunling CHENG Chenghao ZHUANG Yuxi DENG
Zhen WANG Longye WANG
Naohiro TODA Tetsuya NAKAGAMI
Haijun Wang Tao Hu Dongdong Chen Huiwei Yao Runze He Di Wu Zhifu Tian
Jianqiang NI Gaoli WANG Yingxin LI Siwei SUN
Rui CHENG Yun JIANG Qinglin ZHANG Qiaoqiao XIA
Ren TOGO Rintaro YANAGI Masato KAWAI Takahiro OGAWA Miki HASEYAMA
Naoki TATTA Yuki SAKATA Rie JINKI Yuukou HORITA
Kundan LAL DAS Munehisa SEKIKAWA Naohiko INABA
Menglong WU Tianao YAO Zhe XING Jianwen ZHANG Yumeng LIN
Jian ZHANG Zhao GUANG Wanjuan SONG Zhiyan XU
Shinya Matsumoto Daiki Ikemoto Takuya Abe Kan Okubo Kiyoshi Nishikawa
Kazuki HARADA Yuta MARUYAMA Tomonori TASHIRO Gosuke OHASHI
Zezhong WANG Masayuki SHIMODA Atsushi TAKAHASHI
Pierpaolo AGAMENNONE
Jianmao XIAO Jianyu ZOU Yuanlong CAO Yong ZHOU Ziwei YE Xun SHAO
Kazumasa ARIMURA Ryoichi MIYAUCHI Koichi TANNO
Shinichi NISHIZAWA Shinji KIMURA
Zhe LIU Wu GUAN Ziqin YAN Liping LIANG
Shuichi OHNO Shenjian WANG Kiyotsugu TAKABA
Yindong CHEN Wandong CHEN Dancheng HUANG
Xiaohe HE Zongwang LI Wei HUANG Junyan XIANG Chengxi ZHANG Zhuochen XIE Xuwen LIANG
Conggai LI Feng LIU Yingying LI Yanli XU
Siwei Yang Tingli Li Tao Hu Wenzhi Zhao
Takahiro FUJITA Kazuyuki WADA
Kazuma TAKA Tatsuya ISHIKAWA Kosei SAKAMOTO Takanori ISOBE
Quang-Thang DUONG Kohei MATSUKAWA Quoc-Trinh VO Minoru OKADA
Sihua LIU Xiaodong ZHU Kai KANG Li WAN Yong WANG
Kazuya YAMAMOTO Nobukazu TAKAI
Yasuhiro Sugimoto Nobukazu Takai
Ho-Lim CHOI
Weibang DAI Xiaogang CHEN Houpeng CHEN Sannian SONG Yichen SONG Shunfen LI Tao HONG Zhitang SONG
Duo Zhang Shishan Qi
Young Ghyu Sun Soo Hyun Kim Dong In Kim Jin Young Kim
Hongbin ZHANG Ao ZHAN Jing HAN Chengyu WU Zhengqiang WANG
Yuli YANG Jianxin SONG Dan YU Xiaoyan HAO Yongle CHEN
Kazuki IWAHANA Naoto YANAI Atsuo INOMATA Toru FUJIWARA
Rikuto KURAHARA Kosei SAKAMOTO Takanori ISOBE
Elham AMIRI Mojtaba JOODAKI
Qingqi ZHANG Xiaoan BAO Ren WU Mitsuru NAKATA Qi-Wei GE
Jiaqi Wang Aijun Liu Changjun Yu
Ruo-Fei Wang Jia Zhang Jun-Feng Liu Jing-Wei Tang
Yingnan QI Chuhong TANG Haiyang LIU Lianrong MA
Yi XIONG Senanayake THILAK Daisuke ARAI Jun IMAOKA Masayoshi YAMAMOTO
Zhenhai TAN Yun YANG Xiaoman WANG Fayez ALQAHTANI
Chenrui CHANG Tongwei LU Feng YAO
Takuma TSUCHIDA Rikuho MIYATA Hironori WASHIZAKI Kensuke SUMOTO Nobukazu YOSHIOKA Yoshiaki FUKAZAWA
Shoichi HIROSE Kazuhiko MINEMATSU
Toshimitsu USHIO
Yuta FUKUDA Kota YOSHIDA Takeshi FUJINO
Qingping YU Yuan SUN You ZHANG Longye WANG Xingwang LI
Qiuyu XU Kanghui ZHAO Tao LU Zhongyuan WANG Ruimin HU
Lei Zhang Xi-Lin Guo Guang Han Di-Hui Zeng
Meng HUANG Honglei WEI
Yang LIU Jialong WEI Shujian ZHAO Wenhua XIE Niankuan CHEN Jie LI Xin CHEN Kaixuan YANG Yongwei LI Zhen ZHAO
Ngoc-Son DUONG Lan-Nhi VU THI Sinh-Cong LAM Phuong-Dung CHU THI Thai-Mai DINH THI
Lan XIE Qiang WANG Yongqiang JI Yu GU Gaozheng XU Zheng ZHU Yuxing WANG Yuwei LI
Jihui LIU Hui ZHANG Wei SU Rong LUO
Shota NAKAYAMA Koichi KOBAYASHI Yuh YAMASHITA
Wataru NAKAMURA Kenta TAKAHASHI
Chunfeng FU Renjie JIN Longjiang QU Zijian ZHOU
Masaki KOBAYASHI
Shinichi NISHIZAWA Masahiro MATSUDA Shinji KIMURA
Keisuke FUKADA Tatsuhiko SHIRAI Nozomu TOGAWA
Yuta NAGAHAMA Tetsuya MANABE
Baoxian Wang Ze Gao Hongbin Xu Shoupeng Qin Zhao Tan Xuchao Shi
Maki TSUKAHARA Yusaku HARADA Haruka HIRATA Daiki MIYAHARA Yang LI Yuko HARA-AZUMI Kazuo SAKIYAMA
Guijie LIN Jianxiao XIE Zejun ZHANG
Hiroki FURUE Yasuhiko IKEMATSU
Longye WANG Lingguo KONG Xiaoli ZENG Qingping YU
Ayaka FUJITA Mashiho MUKAIDA Tadahiro AZETSU Noriaki SUETAKE
Xingan SHA Masao YANAGISAWA Youhua SHI
Jiqian XU Lijin FANG Qiankun ZHAO Yingcai WAN Yue GAO Huaizhen WANG
Sei TAKANO Mitsuji MUNEYASU Soh YOSHIDA Akira ASANO Nanae DEWAKE Nobuo YOSHINARI Keiichi UCHIDA
Kohei DOI Takeshi SUGAWARA
Yuta FUKUDA Kota YOSHIDA Takeshi FUJINO
Mingjie LIU Chunyang WANG Jian GONG Ming TAN Changlin ZHOU
Hironori UCHIKAWA Manabu HAGIWARA
Atsuko MIYAJI Tatsuhiro YAMATSUKI Tomoka TAKAHASHI Ping-Lun WANG Tomoaki MIMOTO
Kazuya TANIGUCHI Satoshi TAYU Atsushi TAKAHASHI Mathieu MOLONGO Makoto MINAMI Katsuya NISHIOKA
Masayuki SHIMODA Atsushi TAKAHASHI
Yuya Ichikawa Naoko Misawa Chihiro Matsui Ken Takeuchi
Katsutoshi OTSUKA Kazuhito ITO
Rei UEDA Tsunato NAKAI Kota YOSHIDA Takeshi FUJINO
Motonari OHTSUKA Takahiro ISHIMARU Yuta TSUKIE Shingo KUKITA Kohtaro WATANABE
Iori KODAMA Tetsuya KOJIMA
Yusuke MATSUOKA
Yosuke SUGIURA Ryota NOGUCHI Tetsuya SHIMAMURA
Tadashi WADAYAMA Ayano NAKAI-KASAI
Li Cheng Huaixing Wang
Beining ZHANG Xile ZHANG Qin WANG Guan GUI Lin SHAN
Soh YOSHIDA Nozomi YATOH Mitsuji MUNEYASU
Ryo YOSHIDA Soh YOSHIDA Mitsuji MUNEYASU
Nichika YUGE Hiroyuki ISHIHARA Morikazu NAKAMURA Takayuki NAKACHI
Ling ZHU Takayuki NAKACHI Bai ZHANG Yitu WANG
Toshiyuki MIYAMOTO Hiroki AKAMATSU
Yanchao LIU Xina CHENG Takeshi IKENAGA
Kengo HASHIMOTO Ken-ichi IWATA
Hiroshi FUJISAKI
Tota SUKO Manabu KOBAYASHI
Akira KAMATSUKA Koki KAZAMA Takahiro YOSHIDA
Manabu HAGIWARA
This article reviews the author’s group research achievements in analog/mixed-signal circuit and system area with introduction of how they came up with the ideas. Analog/mixed-signal circuits and systems have to be designed as well-balanced in many aspects, and coming up ideas needs some experiences and discussions with researchers. It is also heavily dependent on researchers. Here, the author’s group own experiences are presented as well as their research motivations.
Guangwei CONG Noritsugu YAMAMOTO Takashi INOUE Yuriko MAEGAMI Morifumi OHNO Shota KITA Rai KOU Shu NAMIKI Koji YAMADA
Wide deployment of artificial intelligence (AI) is inducing exponentially growing energy consumption. Traditional digital platforms are becoming difficult to fulfill such ever-growing demands on energy efficiency as well as computing latency, which necessitates the development of high efficiency analog hardware platforms for AI. Recently, optical and electrooptic hybrid computing is reactivated as a promising analog hardware alternative because it can accelerate the information processing in an energy-efficient way. Integrated photonic circuits offer such an analog hardware solution for implementing photonic AI and machine learning. For this purpose, we proposed a photonic analog of support vector machine and experimentally demonstrated low-latency and low-energy classification computing, which evidences the latency and energy advantages of optical analog computing over traditional digital computing. We also proposed an electrooptic Hopfield network for classifying and recognizing time-series data. This paper will review our work on implementing classification computing and Hopfield network by leveraging silicon photonic circuits.
Fumihiko TACHIBANA Huy CU NGO Go URAKAWA Takashi TOI Mitsuyuki ASHIDA Yuta TSUBOUCHI Mai NOZAWA Junji WADATSUMI Hiroyuki KOBAYASHI Jun DEGUCHI
Although baud-rate clock and data recovery (CDR) such as Mueller-Müller (MM) CDR is adopted to ADC-based receivers (RXs), it suffers from false-lock points when the RXs handle PAM4 data pattern because of the absence of edge data. In this paper, a false-lock-aware locking scheme is proposed to address this issue. After the false-lock-aware locking scheme, a clock phase is adjusted to achieve maximum eye height by using a post-1-tap parameter for an FFE in the CDR loop. The proposed techniques are implemented in a 56-Gb/s PAM4 transceiver. A PLL uses an area-efficient “glasses-shaped” inductor. The RX comprises an AFE, a 28-GS/s 7-bit time-interleaved SAR ADC, and a DSP with a 31-tap FFE and a 1-tap DFE. A TX is based on a 7-bit DAC with a 4-tap FFE. The transceiver is fabricated in 16-nm CMOS FinFET technology, and achieves a BER of less than 1e-7 with a 30-dB loss channel. The measurement results show that the MM CDR escapes from false-lock points, and converges to near the optimum point for large eye height.
Satoshi TANAKA Takeshi YOSHIDA Minoru FUJISHIMA
L-type LC/CL matching circuits are well known for their simple analytical solutions and have been applied to many radio-frequency (RF) circuits. When actually constructing a circuit, parasitic elements are added to inductors and capacitors. Therefore, each L and C element has a self-resonant frequency, which affects the characteristics of the matching circuit. In this paper, the parallel parasitic capacitance to the inductor and the series parasitic inductor to the capacitance are taken up as parasitic elements, and the details of the effects of the self-resonant frequency of each element on the S11, voltage standing wave ratio (VSWR) and S21 characteristics are reported. When a parasitic element is added, each characteristic basically tends to deteriorate as the self-resonant frequency decreases. However, as an interesting feature, we found that the combination of resonant frequencies determines the VSWR and passband characteristics, regardless of whether it is the inductor or the capacitor.
Zixuan LI Sangyeop LEE Noboru ISHIHARA Hiroyuki ITO
A wireless sensor terminal module of 5cc size (2.5 cm × 2.5 cm × 0.8 cm) that does not require a battery is proposed by integrating three kinds of circuit technologies. (i) a low-power sensor interface: an FM modulation type CMOS sensor interface circuit that can operate with a typical power consumption of 24.5 μW was fabricated by the 0.7-μm CMOS process technology. (ii) power supply to the sensor interface circuit: a wireless power transmission characteristic to a small-sized PCB spiral coil antenna was clarified and applied to the module. (iii) wireless sensing from the module: backscatter communication technology that modulates the signal from the base terminal equipment with sensor information and reflects it, which is used for the low-power sensing operation. The module fabricated includes a rectifier circuit with the PCB spiral coil antenna that receives wireless power transmitted from base terminal equipment by electromagnetic resonance coupling and converts it into DC power and a sensor interface circuit that operates using the power. The interface circuit modulates the received signal with the sensor information and reflects it back to the base terminal. The module could achieve 100 mm communication distance when 0.4 mW power is feeding to the sensor terminal.
A 150 GHz fundamental oscillator employing an inter-stage matching network based on a transmission line is presented in this letter. The proposed oscillator consists of a two-stage common-emitter amplifier loop, whose inter-stage connections are optimized to meet the oscillation condition. The oscillator is designed in a 130-nm SiGe BiCMOS process that offers fT and fMAX of 350 GHz and 450 GHz. According to simulation results, an output power of 3.17 dBm is achieved at 147.6 GHz with phase noise of -115 dBc/Hz at 10 MHz offset and figure-of-merit (FoM) of -180 dBc/Hz.
Yuyang ZHU Zunsong YANG Masaru OSADA Haoming ZHANG Tetsuya IIZUKA
Self-dithered digital delta-sigma modulators (DDSMs) are commonly used in fractional-N frequency synthesizers due to their ability to eliminate unwanted spurs from the synthesizer’s spectra without requiring additional hardware. However, when operating with a low-bit input, self-dithered DDSMs can still suffer from spurious tones at certain inputs. In this paper, we propose a self-dithered MASH 1-1-1-1 structure to mitigate the spur issue in the self-dithered MASH DDSMs. The proposed self-dithered MASH 1-1-1-1 suppresses the spurs with shaped dithering and achieves 4th order noise shaping.
We address a path planning problem for heterogeneous multi-robot systems under specifications consisting of temporal constraints and routing tasks such as package delivery services. The robots are partitioned into several groups based on their dynamics and specifications. We introduce a concise description of such tasks, called a work, and extend counting LTL to represent such specifications. We convert the problem into an ILP problem. We show that the number of variables in the ILP problem is fewer than that of the existing method using cLTL+. By simulation, we show that the computation time of the proposed method is faster than that of the existing method.
Daichi ISHIKAWA Naoki HAYASHI Shigemasa TAKAI
In this paper, we consider a distributed stochastic nonconvex optimization problem for multiagent systems. We propose a distributed stochastic gradient-tracking method with event-triggered communication. A group of agents cooperatively finds a critical point of the sum of local cost functions, which are smooth but not necessarily convex. We show that the proposed algorithm achieves a sublinear convergence rate by appropriately tuning the step size and the trigger threshold. Moreover, we show that agents can effectively solve a nonconvex optimization problem by the proposed event-triggered algorithm with less communication than by the existing time-triggered gradient-tracking algorithm. We confirm the validity of the proposed method by numerical experiments.
Koichi KITAMURA Koichi KOBAYASHI Yuh YAMASHITA
In cyber-physical systems (CPSs) that interact between physical and information components, there are many sensors that are connected through a communication network. In such cases, the reduction of communication costs is important. Event-triggered control that the control input is updated only when the measured value is widely changed is well known as one of the control methods of CPSs. In this paper, we propose a design method of output feedback controllers with decentralized event-triggering mechanisms, where the notion of uniformly ultimate boundedness is utilized as a control specification. Using this notion, we can guarantee that the state stays within a certain set containing the origin after a certain time, which depends on the initial state. As a result, the number of times that the event occurs can be decreased. First, the design problem is formulated. Next, this problem is reduced to a BMI (bilinear matrix inequality) optimization problem, which can be solved by solving multiple LMI (linear matrix inequality) optimization problems. Finally, the effectiveness of the proposed method is presented by a numerical example.
A PBN is well known as a mathematical model of complex network systems such as gene regulatory networks. In Boolean networks, interactions between nodes (e.g., genes) are modeled by Boolean functions. In PBNs, Boolean functions are switched probabilistically. In this paper, for a PBN, a simplified representation that is effective in analysis and control is proposed. First, after a polynomial representation of a PBN is briefly explained, a simplified representation is derived. Here, the steady-state value of the expected value of the state is focused, and is characterized by a minimum feedback vertex set of an interaction graph expressing interactions between nodes. Next, using this representation, input selection and stabilization are discussed. Finally, the proposed method is demonstrated by a biological example.
Daichi MINAMIDE Tatsuhiro TSUCHIYA
In interdependent systems, such as electric power systems, entities or components mutually depend on each other. Due to these interdependencies, a small number of initial failures can propagate throughout the system, resulting in catastrophic system failures. This paper addresses the problem of finding the set of entities whose failures will have the worst effects on the system. To this end, a two-phase algorithm is developed. In the first phase, the tight bound on failure propagation steps is computed using a Boolean Satisfiablility (SAT) solver. In the second phase, the problem is formulated as an Integer Linear Programming (ILP) problem using the obtained step bound and solved with an ILP solver. Experimental results show that the algorithm scales to large problem instances and outperforms a single-phase algorithm that uses a loose step bound.
Fuma MOTOYAMA Koichi KOBAYASHI Yuh YAMASHITA
Control of complex networks such as gene regulatory networks is one of the fundamental problems in control theory. A Boolean network (BN) is one of the mathematical models in complex networks, and represents the dynamic behavior by Boolean functions. In this paper, a solution method for the finite-time control problem of BNs is proposed using a BDD (binary decision diagram). In this problem, we find all combinations of the initial state and the control input sequence such that a certain control specification is satisfied. The use of BDDs enables us to solve this problem for BNs such that the conventional method cannot be applied. First, after the outline of BNs and BDDs is explained, the problem studied in this paper is given. Next, a solution method using BDDs is proposed. Finally, a numerical example on a 67-node BN is presented.
Tomoki NAKAMURA Naoki HAYASHI Masahiro INUIGUCHI
In this paper, we consider distributed decision-making over directed time-varying multi-agent systems. We consider an adversarial bandit problem in which a group of agents chooses an option from among multiple arms to maximize the total reward. In the proposed method, each agent cooperatively searches for the optimal arm with the highest reward by a consensus-based distributed Exp3 policy. To this end, each agent exchanges the estimation of the reward of each arm and the weight for exploitation with the nearby agents on the network. To unify the explored information of arms, each agent mixes the estimation and the weight of the nearby agents with their own values by a consensus dynamics. Then, each agent updates the probability distribution of arms by combining the Hedge algorithm and the uniform search. We show that the sublinearity of a pseudo-regret can be achieved by appropriately setting the parameters of the distributed Exp3 policy.
Keitaro TSUJI Shun-ichi AZUMA Ikumi BANNO Ryo ARIIZUMI Toru ASAI Jun-ichi IMURA
When a mathematical model is not available for a dynamical system, it is reasonable to use a data-driven approach for analysis and control of the system. With this motivation, the authors have recently developed a data-driven solution to Lyapunov equations, which uses not the model but the data of several state trajectories of the system. However, the number of state trajectories to uniquely determine the solution is O(n2) for the dimension n of the system. This prevents us from applying the method to a case with a large n. Thus, this paper proposes a novel class of data-driven Lyapunov equations, which requires a smaller amount of data. Although the previous method constructs one scalar equation from one state trajectory, the proposed method constructs three scalar equations from any combination of two state trajectories. Based on this idea, we derive data-driven Lyapunov equations such that the number of state trajectories to uniquely determine the solution is O(n).
Qingqi ZHANG Xiaoan BAO Ren WU Mitsuru NAKATA Qi-Wei GE
Automatic detection of prohibited items is vital in helping security staff be more efficient while improving the public safety index. However, prohibited item detection within X-ray security inspection images is limited by various factors, including the imbalance distribution of categories, diversity of prohibited item scales, and overlap between items. In this paper, we propose to leverage the Poisson blending algorithm with the Canny edge operator to alleviate the imbalance distribution of categories maximally in the X-ray images dataset. Based on this, we improve the cascade network to deal with the other two difficulties. To address the prohibited scale diversity problem, we propose the Re-BiFPN feature fusion method, which includes a coordinate attention atrous spatial pyramid pooling (CA-ASPP) module and a recursive connection. The CA-ASPP module can implicitly extract direction-aware and position-aware information from the feature map. The recursive connection feeds the CA-ASPP module processed multi-scale feature map to the bottom-up backbone layer for further multi-scale feature extraction. In addition, a Rep-CIoU loss function is designed to address the overlapping problem in X-ray images. Extensive experimental results demonstrate that our method can successfully identify ten types of prohibited items, such as Knives, Scissors, Pressure, etc. and achieves 83.4% of mAP, which is 3.8% superior to the original cascade network. Moreover, our method outperforms other mainstream methods by a significant margin.
Priyadharshini MOHANRAJ Saravanan PARAMASIVAM
The detection of hardware trojans has been extensively studied in the past. In this article, we propose a side-channel analysis technique that uses a wrapper-based feature selection technique for hardware trojan detection. The whale optimization algorithm is modified to carefully extract the best feature subset. The aim of the proposed technique is multiobjective: improve the accuracy and minimize the number of features. The power consumption traces measured from AES-128 trojan circuits are used as features in this experiment. The stabilizing property of the feature selection method helps to bring a mutual trade-off between the precision and recall parameters thereby minimizing the number of false negatives. The proposed hardware trojan detection scheme produces a maximum of 10.3% improvement in accuracy and reduction up to a single feature by employing the modified whale optimization technique. Thus the evaluation results conducted on various trust-hub cryptographic benchmark circuits prove to be efficient from the existing state-of-art methods.
Jiang HUANG Xianglin HUANG Lifang YANG Zhulin TAO
We present a novel adversarial, end-to-end framework based on Creative-GAN to generate artistic music conditioned on dance videos. Our proposed framework takes the visual and motion posture data as input, and then adopts a quantized vector as the audio representation to generate complex music corresponding to input. However, the GAN algorithm just imitate and reproduce works what humans have created, instead of generating something new and creative. Therefore, we newly introduce Creative-GAN, which extends the original GAN framework to two discriminators, one is to determine whether it is real music, and the other is to classify music style. The paper shows that our proposed Creative-GAN can generate novel and interesting music which is not found in the training dataset. To evaluate our model, a comprehensive evaluation scheme is introduced to make subjective and objective evaluation. Compared with the advanced methods, our experimental results performs better in measureing the music rhythm, generation diversity, dance-music correlation and overall quality of generated music.
Qingping YU You ZHANG Zhiping SHI Xingwang LI Longye WANG Ming ZENG
In this letter, a deep neural network (DNN) aided joint source-channel (JSCC) decoding scheme is proposed for polar codes. In the proposed scheme, an integrated factor graph with an unfolded structure is first designed. Then a DNN aided flooding belief propagation decoding (FBP) algorithm is proposed based on the integrated factor, in which both source and channel scaling parameters in the BP decoding are optimized for better performance. Experimental results show that, with the proposed DNN aided FBP decoder, the polar coded JSCC scheme can have about 2-2.5 dB gain over different source statistics p with source message length NSC = 128 and 0.2-1 dB gain over different source statistics p with source message length NSC = 512 over the polar coded JSCC system with existing BP decoder.
The very high path loss caused by molecular absorption becomes the biggest problem in Terahertz (THz) wireless communications. Recently, the multi-band ultra-massive multi-input multi-output (UM-MIMO) system has been proposed to overcome the distance problem. In UM-MIMO systems, the impact of mutual coupling among antennas on the system performance is unable to be ignored because of the dense array. In this letter, a channel model of UM-MIMO communication system is developed which considers coupling effect. The effect of mutual coupling in the subarray on the functionality of the system has been investigated through simulation studies, and reliable results have been derived.