We describe the development of single-flux-quantum (SFQ) microprocessors and the related technologies such as designing, circuit architecture, microarchitecture, etc. Since the microprocessors studied here aim for a general-purpose computing system, we employ the complexity-reduced (CORE) architecture in which the high-speed nature of the SFQ circuits is used not for increasing processor performance but for reducing the circuit complexity. The bit-serial processing is the most suitable way to realize the CORE architecture. We assembled all the best technologies concerning SFQ integrated circuits and designed the SFQ microprocessors, CORE1α, CORE1β, and CORE1γ. The CORE1β was made up of about 11000 Josephson junctions and successfully demonstrated. The peak performance reached 1400 million operations per second with a power consumption of 3.4 mW. We showed that the SFQ microprocessors had an advantage in a performance density to semiconductor's ones, which lead to the potential for constructing a high performance SFQ-circuit-based computing system.

In a power grid used to distribute electricity, optical fibers can be inserted inside overhead ground wires to form an optical network infrastructure for data communications. Dense wavelength division multiplexing (DWDM)-based optical networks present a promising approach to achieve a scalable backbone network for power grids. This paper proposes a complete optimization procedure for optical network designs based on an existing power grid. We design a network as a subgraph of the power grid and divide the network topology into two layers: backbone and access networks. The design procedure includes physical topology design, routing and wavelength assignment (RWA) and optical amplifier placement. We formulate the problem of topology design into two steps: selecting the concentrator nodes and their node members, and finding the connections among concentrators subject to the two-connectivity constraint on the backbone topology. Selection and connection of concentrators are done using integer linear programming (ILP). For RWA and optical amplifier placement problem, we solve these two problems together since they are closely related. Since the ILP for solving these two problems becomes intractable with increasing network size, we propose a simulated annealing approach. We choose a neighborhood structure based on path-switching operations using k shortest paths for each source and destination pair. The optimal number of optical amplifiers is solved based on local search among these neighbors. We solve and present some numerical results for several randomly generated power grid topologies.

In this paper, a block-constrained trellis coded quantization (BC-TCQ) algorithm is combined with an algebraic codebook to produce an algebraic trellis code (ATC) to be used in ACELP coding. In ATC, the set of allowed algebraic codebook pulse positions is expanded, and the expanded set is partitioned into subsets of pulse positions; the trellis branches are labeled with these subsets. The list Viterbi algorithm (LVA) is used to select the excitation codevector. The combination of an ATC codebook and LVA trellis search algorithm is denoted as an ATC-LVA block code. The ATC-LVA block code is used as the fixed codebook of the AMR-WB 8.85 kbps mode, reducing complexity compared to the conventional algebraic codebook.

We have designed a superconductor-semiconductor hybrid analog-to-digital (A/D) converter and experimentally evaluated its performance at sampling frequencies up to 18.6 GHz. The A/D converter consists of a superconductor front-end circuit and a semiconductor back-end circuit. The front-end circuit includes a sigma-delta modulator and an interface circuit, which is for transmitting data signal to the semiconductor back-end circuit. The semiconductor back-end circuit performs decimation filtering. The design of the modulator was modified to reduce effects of integrator leak and thermal noise on signal-to-noise ratio (SNR). Using the improved modulator design, we achieved a bit-accuracy close to the ideal value. The hybrid architecture enabled us to reduce the integration scale of the front-end circuit to fewer than 500 junctions. This simplicity makes feasible a circuit based on a high TC superconductor as well as on a low TC superconductor. The experimental results show that the hybrid A/D converter operated perfectly and that SNR was 84.8 dB (bit accuracy~13.8 bit) at a band width of 9.1 MHz. This converter has the highest performance of all sigma-delta A/D converters.

This paper addresses the problem of voice activity detection (VAD) in noisy environments. The VAD method proposed in this paper is based on a statistical model approach, and estimates statistical models sequentially without a priori knowledge of noise. Namely, the proposed method constructs a clean speech / silence state transition model beforehand, and sequentially adapts the model to the noisy environment by using a switching Kalman filter when a signal is observed. In this paper, we carried out two evaluations. In the first, we observed that the proposed method significantly outperforms conventional methods as regards voice activity detection accuracy in simulated noise environments. Second, we evaluated the proposed method on a VAD evaluation framework, CENSREC-1-C. The evaluation results revealed that the proposed method significantly outperforms the baseline results of CENSREC-1-C as regards VAD accuracy in real environments. In addition, we confirmed that the proposed method helps to improve the accuracy of concatenated speech recognition in real environments.

Users require speech recognition systems that offer rapid response and high accuracy concurrently. Speech recognition accuracy is degraded by additive noise, imposed by ambient noise, and convolutional noise, created by space transfer characteristics, especially in distant talking situations. Against each type of noise, existing model adaptation techniques achieve robustness by using HMM-composition and CMN (cepstral mean normalization). Since they need an additive noise sample as well as a user speech sample to generate the models required, they can not achieve rapid response, though it may be possible to catch just the additive noise in a previous step. In the previous step, the technique proposed herein uses just the additive noise to generate an adapted and normalized model against both types of noise. When the user's speech sample is captured, only online-CMN need be performed to start the recognition processing, so the technique offers rapid response. In addition, to cover the unpredictable S/N values possible in real applications, the technique creates several S/N HMMs. Simulations using artificial speech data show that the proposed technique increased the character correct rate by 11.62% compared to CMN.

In optical burst switching (OBS) networks, burst with different numbers of hops experience unfairness in terms of the burst loss probability. In this paper, we propose a preemptive scheme based on the number of transit hops in OBS networks. In our proposed scheme, preemption is performed with two thresholds; one is for the total number of hops of a burst and the other is for the number of transit hops the burst has passed through. We evaluate the performance of the scheme by simulation, and numerical examples show that the proposed scheme improves the fairness among the bursts with different numbers of hops, keeping the overall burst loss probability the same as that for the conventional OBS transmission without preemption.

This letter presents a race-free mixed serial-parallel comparison (RFMSPC) scheme which uses both serial and parallel CAMs in a match line. A self-reset search line scheme for the serial CAM is proposed to avoid the timing race problem and additional timing penalties. Various 32 entry CAMs are designed using 90 nm 1.2 V CMOS process to verify the proposed RFMSPC scheme. It shows that the RFMSPC saves power consumption by 40%, 53% and 63% at the cost of a 4%, 6% and 16% increase in search time according to 1, 2, and 4 serial CAM bits in a match line.

Learning for boltzmann machines deals with each state individually. If given data is categorized, the probabilities have to be distributed to each state, not to each catetory. We propose boltzmann machines identifying the states in the same categories. Boltzmann machines with hidden units are the special cases. Boltzmann learning and em algorithm are effective learning methods for boltzmann machines. We solve boltzmann learning and em algorithm for the proposed models.

This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i.e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.

In this paper, we analyze the effects of IQ (In-phase/Quadrature-phase) imbalance at both transmitter and receiver of OFDM (Orthogonal Frequency Division Multiplexing) system and show that more diversity gain can be achieved even though there are unwanted IQ imbalance. When mixed sub-carriers within an OFDM symbol due to the IQ imbalance undergo frequency selective channels, additional diversity effects are expected during the demodulation process. Simulation results on the symbol error rate (SER) performance with ML (Maximum Likelihood) and OSIC (Ordered Successive Interference Cancellation) receiver show that significant performance gain can be achieved with the diversity gain caused by the IQ imbalance combined with the frequency selective channels.

In recent decades, there has been a great deal of research into the problem of bilingual speech recognition - to develop a recognizer that can handle inter- and intra-sentential language switching between two languages. This paper presents our recent work on the development of a grammar-constrained, Mandarin-English bilingual Speech Recognition System (MESRS) for real world music retrieval. Two of the main difficult issues in handling the bilingual speech recognition systems for real world applications are tackled in this paper. One is to balance the performance and the complexity of the bilingual speech recognition system; the other is to effectively deal with the matrix language accents in embedded language. In order to process the intra-sentential language switching and reduce the amount of data required to robustly estimate statistical models, a compact single set of bilingual acoustic models derived by phone set merging and clustering is developed instead of using two separate monolingual models for each language. In our study, a novel Two-pass phone clustering method based on Confusion Matrix (TCM) is presented and compared with the log-likelihood measure method. Experiments testify that TCM can achieve better performance. Since potential system users' native language is Mandarin which is regarded as a matrix language in our application, their pronunciations of English as the embedded language usually contain Mandarin accents. In order to deal with the matrix language accents in embedded language, different non-native adaptation approaches are investigated. Experiments show that model retraining method outperforms the other common adaptation methods such as Maximum A Posteriori (MAP). With the effective incorporation of approaches on phone clustering and non-native adaptation, the Phrase Error Rate (PER) of MESRS for English utterances was reduced by 24.47% relatively compared to the baseline monolingual English system while the PER on Mandarin utterances was comparable to that of the baseline monolingual Mandarin system. The performance for bilingual utterances achieved 22.37% relative PER reduction.

A new adaptive filter algorithm based on the linear prediction property of sinusoidal signals is proposed for unbiased estimation of the frequency of a real tone in white noise. Similar to the least mean square algorithm, the estimator is computationally simple and it provides unbiased as well as direct frequency measurements. Learning behavior and variance of the estimated frequency are derived and confirmed by computer simulations.

We consider a data set in which each example is an n-dimensional Boolean vector labeled as true or false. A pattern is a co-occurrence of a particular value combination of a given subset of the variables. If a pattern appears frequently in the true examples and infrequently in the false examples, we consider it a good pattern. In this paper, we discuss the problem of determining the data size needed for removing "deceptive" good patterns; in a data set of a small size, many good patterns may appear superficially, simply by chance, independently of the underlying structure. Our hypothesis is that, in order to remove such deceptive good patterns, the data set should contain a greater number of examples than that at which a random data set contains few good patterns. We justify this hypothesis by computational studies. We also derive a theoretical upper bound on the needed data size in view of our hypothesis.

This paper presents a target location estimation method that can use a pair of leaky coaxial cables to determine the 2D coordinates of the target. Since convention location techniques using leaky coaxial cables can find a target location along the cable in 1D, they have been unable to locate it in 2D planes. The proposed method enables us to estimate target on a 2D plane using; 1) a beam-forming technique and 2) a reconstruction technique based on Hough transform. Leaky coaxial cables are equipped with numerous slots at regular interval, which can be utilized as antenna arrays that acts both as transmitters and receivers. By completely exploiting this specific characteristic of leaky coaxial cables, we carried out an antenna array analysis that performs in a beam-forming fashion. Simulation and experimental results support the effectiveness of the proposed target location method.

We propose a fast decoding algorithm for the p-ary first-order Reed-Muller code guaranteeing correction of up to errors and having complexity proportional to nlog n, where n = pm is the code length and p is an odd prime. This algorithm is an extension in the complex domain of the fast Hadamard transform decoding algorithm applicable to the binary case.

With the increasing complexity of LSI, Built-In Self Test (BIST) is a promising technique for production testing. We herein propose a method for diagnosing multiple stuck-at faults based on the compressed responses from BIST. We refer to fault diagnosis based on the ambiguous test pattern set obtained by the compressed responses of BIST as post-BIST fault diagnosis [1]. In the present paper, we propose an effective method by which to perform post-BIST fault diagnosis for multiple stuck-at faults. The efficiency of the success ratio and the feasibility of diagnosing large circuits are discussed.

In order to achieve the prioritized quality of service (QoS) guarantee, the IEEE 802.11e EDCAF (the enhanced distributed channel access function) provides the distinguished services by configuring the different QoS parameters to different access categories (ACs). An admission control scheme is needed to maximize the utilization of wireless channel. Most of papers study throughput improvement by solving the complicated multidimensional Markov-chain model. In this paper, we introduce a backoff model to study the transmission probability of the different arbitration interframe space number (AIFSN) and the minimum contention window size (CWmin). We propose an adaptive control scheme (ACS) to dynamically update AIFSN and CWmin based on the periodical monitoring of current channel status and QoS requirements to achieve the specific service differentiation at access points (AP). This paper provides an effective tuning mechanism for improving QoS in WLAN. Analytical and simulation results show that the proposed scheme outperforms the basic EDCAF in terms of throughput and service differentiation especially at high collision rate.

We present a multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online adaptive estimation is shown to be effective for speech spectral estimation in noisy environments. Furthermore, the multi-channel information in terms of cross-channel statistics are shown to be useful to better adapt the prior distribution parameters to the actual observation, resulting in better performance of speech enhancement algorithm. We tested the proposed algorithm in an in-car speech database and obtained significant improvements of the speech recognition performance, particularly under non-stationary noise conditions such as music, air-conditioner and open window.

A lightweight and high gain planar antenna for space use is realized with radial waveguide slotted array and honeycomb structure with the weight of 1.16 kg and the diameter of 920.5 mm. The slot coupling is analyzed by method of moments considering the hybrid mode in the multi-layer waveguide structure. The propagation constant of the honeycomb structure is measured and the low-loss property is obtained at the frequency range of 8 GHz. The fabricated RLSA is measured and the reflection is around -10 dB in 8 GHz band. The measured aperture fields agree with the calculation in the radial direction. In the azimuthal direction, on the other hand, the fields show ripples of 6 dB and 60 degree. The gain of 35.9 dBi with the efficiency of 58.7% is obtained at 8.6 GHz.