This invited paper is dedicated to introduce recent activities of Japanese microwave industries. 7 topics are introduced from major microwave companies in Japan. All topics are from invited talks in 2014 Asia-Pacific microwave conference (APMC2014) held in Sendai, November, 2014.

In this letter, we study the R-D properties of independent sources based on MSE and SSIM, and compare the bit allocation performance under the MINAVE and MINMAX criteria in video encoding. The results show that MINMAX has similar results in terms of average distortion with MINAVE by using SSIM, which illustrates the consistency between these two criteria in independent perceptual video coding. Further more, MINMAX results in lower quality fluctuation, which shows its advantage for perceptual video coding.

This paper describes an evaluation of a temporally stable spectral envelope estimator proposed in our past research. The past research demonstrated that the proposed algorithm can synthesize speech that is as natural as the input speech. This paper focuses on an objective comparison, in which the proposed algorithm is compared with two modern estimation algorithms in terms of estimation performance and temporal stability. The results show that the proposed algorithm is superior to the others in both aspects.

It is not easy to provide energy supply based on renewable energy enough to satisfy energy demand anytime and anywhere because the amount of renewable energy depends on geographical conditions and the time of day. In order to maximize the satisfaction of energy demand by renewable energy, surplus energy generated with renewable energy should be stored in batteries, and transmitted to electric loads with high demand somewhere in the electricity system. This paper proposes a novel autonomous decentralized mechanism of energy interchanges between distributed batteries on the basis of the diffusion equation and MCMC (Markov Chain Monte Carlo) for realizing energy supply appropriately for energy demand. Experimental results show that the proposed mechanism effectively works under several situations. Moreover, we discuss a method to easily estimate the behavior of the entire system by each node with the proposed mechanism, and the application potentiality of this estimating method to an efficient method working with non-renewable generators while minimizing the dependence of non-renewable energy, and an incentive mechanism to prevent monopolizing energy in systems.

In this letter, high quality speech reconstruction approaches from Mel-frequency cepstral coefficients (MFCC) are presented. Taking into account of the nonnegative and sparse properties of the speech power spectrum, an alternating direction method of multipliers (ADMM) based nonnegative l2 norm (NL2) and weighted nonnegative l2 norm (NWL2) minimization approach is proposed to cope with the under-determined nature of the reconstruction problem. The phase spectrum is recovered by the well-known LSE-ISTFTM algorithm. Experimental results demonstrate that the NL2 and NWL2 approach substantially achieves better quality for reconstructed speech than the conventional l2 norm minimization approach, it sounds very close to the original speech when using the high-resolution MFCC, the PESQ score reaches 4.0.

Magnetic resonant coupling between two coils allows effective wireless transfer of power over distances in the range of tens of centimeters to a few meters. The strong resonant magnetic field also extends to the immediate surroundings of the power transfer system. When a user or bystander is exposed to this magnetic field, electric fields are induced in the body. For the purposes of human and product safety, it is necessary to evaluate whether these fields satisfy the human exposure limits specified in international guidelines and standards. This work investigates the effectiveness of the quasistatic approximation for computational modeling human exposure to the magnetic fields of wireless power transfer systems. It is shown that, when valid, this approximation can greatly reduce the computational requirements of the assessment of human exposure. Using the quasistatic modeling approach, we present an example of the assessment of human exposure to the non-uniform magnetic field of a realistic WPT system for wireless charging of an electric vehicle battery, and propose a coupling factor for practical determination of compliance with the international exposure standards.

Breast cancer is a serious disease across the world, and it is one of the largest causes of cancer death for women. The traditional diagnosis is not only time consuming but also easily affected. Hence, artificial intelligence (AI), especially neural networks, has been widely used to assist to detect cancer. However, in recent years, the computational ability of a neuron has attracted more and more attention. The main computational capacity of a neuron is located in the dendrites. In this paper, a novel neuron model with dendritic nonlinearity (NMDN) is proposed to classify breast cancer in the Wisconsin Breast Cancer Database (WBCD). In NMDN, the dendrites possess nonlinearity when realizing the excitatory synapses, inhibitory synapses, constant-1 synapses and constant-0 synapses instead of being simply weighted. Furthermore, the nonlinear interaction among the synapses on a dendrite is defined as a product of the synaptic inputs. The soma adds all of the products of the branches to produce an output. A back-propagation-based learning algorithm is introduced to train the NMDN. The performance of the NMDN is compared with classic back propagation neural networks (BPNNs). Simulation results indicate that NMDN possesses superior capability in terms of the accuracy, convergence rate, stability and area under the ROC curve (AUC). Moreover, regarding ROC, for continuum values, the existing 0-connections branches after evolving can be eliminated from the dendrite morphology to release computational load, but with no influence on the performance of classification. The results disclose that the computational ability of the neuron has been undervalued, and the proposed NMDN can be an interesting choice for medical researchers in further research.

Modern processors use Branch Target Buffer (BTB)[1] to relax control dependence. Unfortunately, the energy consumption of the BTB is high. In order to effectively fetch instructions, it is necessary to perform a branch prediction at the fetch stage, regardless of whether the fetched instruction is a branch or a nonbranch. Therefore, the number of accesses to the BTB is large, and the energy consumption of the BTB is high. However, accesses from nonbranches to the BTB waste energy. In this paper, we focus on accesses from nonbranches to the BTB, which we call useless accesses from a viewpoint of power. For reducing energy consumption without performance loss, we present a method that reduces useless accesses by using information that indicates whether a fetched instruction is a branch or not. To realize the above approach, we propose a branch bit called B-Bit. A B-Bit is associated with an instruction and indicates whether it is a branch or not. A B-Bit is available at the beginning of the fetch stage. If a B-Bit is “1” signifying a branch, the BTB is accessed. If a B-Bit is “0” signifying a nonbranch, the BTB is not accessed. The experimental results show that the total energy consumption can be reduced by 54.3% without performance loss.

Current mobile communication terminals are equipped with multiple RF circuits that cover all frequency bands assigned for the communication. In order to make efficient use of frequency spectrum and to reduce circuits in a terminal, a low-loss reconfigurable RF filter is necessary to flexibly change RF frequencies. In this paper, a new reconfigurable bandpass filter (BPF) having eight-frequency (three-bit) selection capability is proposed. It employs branch-line switched type variable resonators that provide low insertion loss. One of the design issues is how to control pass bandwidths among selectable frequencies. In order to analyze the bandwidth variation of the reconfigurable BPF, we calculate the changes of external Q and coupling coefficients. It is shown that the inductive coupling design can achieve less variation of bandwidth for the reconfigurable BPF, compared with commonly used capacitive coupling design. A prototype BPF on a printed circuit board with high dielectric constant substrate has been fabricated and evaluated in 2 GHz bands. It presents performance very close to the design results with respect to insertion loss, center frequency and passband bandwidth. Low insertion loss of less than 1 dB is achieved among the eight frequencies.

This paper shows that the induced peak voltage on the short monopole antenna by the EM field radiated from a small gap discharge when the gap width was experimentally changed from 10 to 360µm was not directly proportional to the discharge voltage between the gap. It was found that the 10mm short monopole antenna induced peak voltage had a peak value between 40 and 60µm gap width.

This paper presents a new way to classify different radiation sources by the parameter of directivity, which is a characteristic parameter of electromagnetic radiation sources. The parameter can be determined from measurements of the electric field intensity radiating in all directions in space. We develop three basic antenna models, which are for 3GHz operation, and set 125,000 groups of cube receiving arrays along the main lobe of their radiation patterns to receive the data of far field electric intensity in groups. Then the Back Propagation (BP) neural network and the Support Vector Machine (SVM) method are adopted to analyze training data set, and build and test the classification model. Owing to the powerful nonlinear simulation ability, the SVM method offers higher classification accuracy than the BP neural network in noise environment. At last, the classification model is comprehensively evaluated in three aspects, which are capability of noise immunity, F1 measure and the normalization method.

String-topology multi-hop network is often selected as an analysis object because it is one of the fundamental network topologies. The purpose of this paper is to establish expression for end-to-end delay for IEEE 802.11 string-topology multi-hop networks. For obtaining the analytical expression, the effects of frame collisions and carrier-sensing effect from other nodes under the non-saturated condition are obtained for each node in the network. For expressing the properties in non-saturated condition, a new parameter, which is frame-existence probability, is defined. The end-to-end delay of a string-topology multi-hop network can be derived as the sum of the transmission delays in the network flow. The analytical predictions agree with simulation results well, which show validity of the obtained analytical expressions.

This paper presents the detailed investigations on a simple multi-band method that allows inverted-F antennas (IFAs) to achieve good impedance matching in many different frequency bands. The impressive simplicity of the method arises from its sharing of a shorting strip among multiple branch elements to simultaneously generate independent resonant modes at arbitrary frequencies. Our simulation and measurement results clarify that, by adjusting the number of branch elements and their lengths, it is very easy to control both the total number of resonant modes and the position of each resonant frequency with impedance matching improved concurrently by adjusting properly the distance ds between the feeding and shorting points. The effectiveness of the multi-band method is verified in antenna miniaturization designs, not only in the case of handset antenna, but also in the design upon an infinite ground plane. Antenna performance and operation principles of proposed multi-band models in each case are analyzed and discussed in detail.

Recently, among MIMO-OFDM detection schemes, a lot of V-BLAST schemes have been suggested in order to achieve high data rate. Therefore signal detection of MIMO-OFDM system is important issue. In this letter, extended DFE detection scheme is proposed. According to simulation result, the extended DFE detection has similar performance with QRD-M detection but the complexity is about 24.02% of QRD-M detection. Therefore the proposed E-DFE detection can be efficiently used in MIMO-OFDM system.

This paper reports on the trending literature of occlusion handling in the task of online visual tracking. The discussion first explores visual tracking realm and pinpoints the necessity of dedicated attention to the occlusion problem. The findings suggest that although occlusion detection facilitated tracking impressively, it has been largely ignored. The literature further showed that the mainstream of the research is gathered around human tracking and crowd analysis. This is followed by a novel taxonomy of types of occlusion and challenges arising from it, during and after the emergence of an occlusion. The discussion then focuses on an investigation of the approaches to handle the occlusion in the frame-by-frame basis. Literature analysis reveals that researchers examined every aspect of a tracker design that is hypothesized as beneficial in the robust tracking under occlusion. State-of-the-art solutions identified in the literature involved various camera settings, simplifying assumptions, appearance and motion models, target state representations and observation models. The identified clusters are then analyzed and discussed, and their merits and demerits are explained. Finally, areas of potential for future research are presented.

RF under sampling is more suitable for Satellite receiver systems in comparison to terrestrial systems. In conventional RF under sampling the minimum sampling frequency (fs) should be atleast twice the system bandwidth; therefore for a system with a wide bandwidth, a relatively high fs is necessary. In this paper we propose a direct RF under sampling reception method that halves fs. The proposed f's is achieved by folding in band noise in half. A method of adapting f's for the reception of signals in different channels is also proposed; this ensures that the SNR is not degraded for any channel. To evaluate the proposed technique's performance and compare it to the conventional case a 3 channel, 1 GHz band test receiver and it's key device (i.e. S/H circuit) are developed. Using SNR and EVM as performance indexes, the performance of the proposed technique has been evaluated and compared to that of the conventional technique. The evaluation results show that the proposed technique can achieve the same performance as conventional RF under sampling for all 3 channels, using only half of the sampling frequency of the conventional technique.

Multiple-way (N-way) asynchronous arbitration is an important issue in asynchronous system design. In this paper, novel implementation methods of N-way asynchronous arbiters are presented. We first present N-way rectangle mesh arbiters using 2-way mutual exclusion elements. Then, N-way token-ring arbiters based on the non-return-to-zero signaling is also presented. The former can issue grant signals with the same percentage for all the arriving request signals while the latency is proportional to the number of inputs. The latter can achieve low latency and low energy arbitration for a heavy workload environment and a large number of inputs. In this paper, we compare their performances using the 28nm FD-SOI process technologies qualitatively and quantitatively.

This paper presents a novel CMOS bias topology serving as not only a bias circuit but also an adaptive linearizer for SiGe HBT power amplifier (PA) IC. The novel bias circuit can well keep the base-to-emitter voltage (Vbe) of RF amplifying HBT constant and adaptively increase the base current (Ib) with the increase of the input power. Therefore, the gain compression and phase distortion performance of the PA is improved. A three-stage 5-GHz band PA IC with the novel bias circuit for WLAN applications is designed and fabricated in IBM 0.35µm SiGe BiCMOS technology. Under 54Mbps OFDM signal at 5.4GHz, the PA IC exhibits a measured small-signal gain of 29dB, an EVM of 0.9% at 17dBm output power and a DC current consumption of 284mA.

Novel multi-band mixers that can receive multiple band signals concurrently are proposed and evaluated. The mixers achieve independent gain control through novel relative power control method of the multiple local oscillator (LO) signals. Linear control is also achieved through multiple LO signal input with total LO power control. Theoretical analysis shows that odd-order nonlinearity components of the multiple LO signals support linear conversion gain control. Dual- and triple-band tests are conducted using typical three MOSFET mixers fabricated by a 0.25 µm SiGe BiCMOS process. Measurements confirm over 40 dB independent control of conversion gain, linear control achieved through LO input power control. The proposed mixers have high input linearity with a 5 dBm output third intercept point. A method is also proposed to reduce interference caused by mixing between multiple LO signals.

In traditional speech emotion recognition systems, when the training and testing utterances are obtained from different corpora, the recognition rates will decrease dramatically. To tackle this problem, in this letter, inspired from the recent developments of sparse coding and transfer learning, a novel sparse transfer learning method is presented for speech emotion recognition. Firstly, a sparse coding algorithm is employed to learn a robust sparse representation of emotional features. Then, a novel sparse transfer learning approach is presented, where the distance between the feature distributions of source and target datasets is considered and used to regularize the objective function of sparse coding. The experimental results demonstrate that, compared with the automatic recognition approach, the proposed method achieves promising improvements on recognition rates and significantly outperforms the classic dimension reduction based transfer learning approach.