In this paper, a method of detecting overlapping speech segments in meetings is proposed. It is known that the eigenvalue distribution of the spatial correlation matrix calculated from a multiple microphone input reflects information on the number and relative power of sound sources. However, in a reverberant sound field, the feature of the number of sources in the eigenvalue distribution is degraded by the room reverberation. In the Support Vector Machines approach, the eigenvalue distribution is classified into two classes (overlapping speech segments and single speech segments). In the Support Vector Regression approach, the relative power of sound sources is estimated by using the eigenvalue distribution, and overlapping speech segments are detected based on the estimated relative power. The salient feature of this approach is that the sensitivity of detecting overlapping speech segments can be controlled simply by changing the threshold value of the relative power. The proposed method was evaluated using recorded data of an actual meeting.

In this paper, analysis and synthesis methods of emotional voice for man-machine natural interface is developed. First, the emotional voice (neutral, anger, sadness, joy, dislike) is analyzed using time-frequency representation of speech and similarity analysis. Then, based on the result of emotional analysis, a voice with neutral emotion is transformed to synthesize the particular emotional voice using time-frequency modifications. In the simulations, five types of emotion are analyzed using 50 samples of speech signals. The high average discrimination rate is achieved in the similarity analysis. Further, the synthesized emotional voice is subjectively evaluated. It is confirmed that the emotional voice is naturally generated by the proposed time-frequency based approach.

Breaking arcs are generated between a pair of Cu electrical contacts in a DC 42 V/10.5 A circuit, and the arc voltage, the arc current and the time-resolved arc spectral intensities near contact surfaces are simultaneously measured. The arc temperature is calculated from some spectral intensities emitted from Cu neutral atoms using the Boltzmann plot method. The arc temperatures near the cathode and anode surfaces are measured, and the following experimental results were obtained. (1) Time evolutions of the spectral intensities and the calculated arc temperature have similar characteristics. (2) The arc temperature near the anode surface is higher than that near the cathode surface, and the temperature fluctuation near the anode surface is larger than that near the cathode. (3) Just before arc extinction, the arc temperature near the cathode surface is almost constant for many breaking operations but the arc temperature near the anode surface varies.

The convergence speed of the conventional adaptive LMS algorithms for time delay estimation (TDE) is highly dependent on the spectral distribution of the desired random source signals of interest, thus the performance of TDE might be degraded, dramatically. To solve this problem, in this letter, a DCT-transform domain constrained adaptive normalized-LMS filtering scheme, referred to as the adaptive constrained DCT-LMS algorithm, is devised for TDE. Computer simulation results verify that the proposed scheme can be used to achieve desired performance, for input random signals with different spectral distributions; it outperforms the unconstrained DCT-LMS and time-domain constrained adaptive LMS algorithms.

Breaking arcs occurring between silver electrical contacts are observed in DC42 V resistive circuit using a high-speed camera. The motion and current densities of the cathode and anode spot regions are investigated for different interrupt currents (I=7 A, 10 A and 14 A). Results indicate that the arc length at which the motion of arc spots becomes stable depends on the interrupt current, and the current densities of the cathode spot region are almost constant immediately before arc extinction for each interrupt current.

To achieve a very high data rate within a limited frequency band in orthogonal frequency division multiplexing (OFDM) systems, multi-input multi-output (MIMO) techniques are very promising. Moreover, if a transmitter has the channel state information (CSI), the achievable spectrum efficiency can be maximized using the eigenbeam-space division multiplexing (E-SDM). However, this scheme demands accurate channel estimation. Therefore, in a closed-loop transmission scheme, an increase in the amount of feedback is absolutely necessary for the E-SDM. This paper describes a downlink beamforming method that significantly reduces the amount of feedback needed by using the common transmission weight vectors in all sub-carriers, compared to the amount required for E-SDM. The proposed method also applies transmission diversity to compensate for the quality. The effectiveness of the proposed method was confirmed using computer simulations in both Ricean and Rayleigh fading environments.

This paper analytically studies performance improvement achieved by packet dispersion. Contrary to the previous work on packet dispersion, we consider the tail distribution of queue length and that of packet delay as performance measures, and we model a packet network as multiple parallel queues where the arrival processes from sources are not renewal but highly bursty. To appropriately evaluate the performance improvement achieved by packet dispersion, we develop approximate formulas to estimate the tail distributions. Our approximate formulas yield more accurate estimations than the standard approximate formulas. In the numerical results, we observe that packet dispersion can greatly improve the delay performance of packets. We also see that packet-level load balancing is superior to flow-level load balancing for any distribution ratio.

If a logic circuit was specialized to a specific input, the derived circuit would be faster and smaller than the original. This study presents various designs of a key-specific AES encryption circuit. In our iterative design, 41% of the logic gates and 20% of RAM were reduced, while 24% more performance was derived. In our pipelined design, 54% of the logic gates and 20% of RAM were reduced, while 74% higher performance was achieved. The results on DES encryption circuits are also presented for comparison.

We propose a novel strategy to obtain a high spatio-temporal resolution video. To this end, we introduce a dual sensor camera that can capture two video sequences with the same field of view simultaneously. These sequences record high resolution with low frame rate and low resolution with high frame rate. This paper presents an algorithm to synthesize a high spatio-temporal resolution video from these two video sequences by using motion compensation and spectral fusion. We confirm that the proposed method improves the resolution and frame rate of the synthesized video.

Various mixed-signal very-high-speed integrated circuits have been developed using InP DHBTs. These circuits have been designed for fiber-optic 43 Gbit/s transmissions applications. They include: on the transmitting side, a clocked driver and an EAM driver, as well as a PSBT/DQPSK precoder; on the receiving side, a sensitive decision circuit, a limiting amplifier and an eye monitor. System experiments made possible by these circuits include a 6 Tbit/s transmission on >6000 km distance.

We extend a graph spectral method for extracting clusters from graphs representing pairwise similarity between data to hypergraph data with hyperedges denoting higher order similarity between data. Our method is robust to noisy outlier data and the number of clusters can be easily determined. The unsupervised method extracts clusters sequentially in the order of the majority of clusters. We derive from the unsupervised algorithm a semi-supervised one which can extract any cluster irrespective of its majority. The performance of those methods is exemplified with synthetic toy data and real image data.

This paper proposes a gonio-spectral imaging system for measuring light reflection on an object surface by using two robot arms, a multi-band lighting system, and a monochrome digital camera. It allows four degrees of freedom in incident and viewing angles necessary for full parametrization of a reflection model function. Spectral images captured for various incident and viewing angles are warped as if they were all captured from the same viewing direction. The intensity of reflected light is thus recorded in a normalized image form for any incident and viewing directions. The normalized images are used to estimate reflection model parameters at each surface point. To ensure point-wise reflection modeling, a calibration method is also proposed based on a geometrical model of the robot arms and camera. The proposed system can deal with objects with surface texture. Experiments are done on system calibration, reflection model, and spectral estimation. The results using colored objects show the feasibility of the proposed imaging system.

In this letter we present steady-state analyses of a gradient algorithm (GA) for second-order adaptive infinite impulse response (IIR) notch filters. A method for deriving more accurate estimation mean square error (MSE) expressions than the recently proposed method is presented. The method is based on the estimation error power spectral density (PSD). Moreover, an expression for the estimation bias for the adaptive IIR notch filter with constrained poles and zeros is shown to be obtained from the estimation MSE expression. Simulations are presented to confirm the validity of the analyses.

With advent of the ubiquitous network era and due to recent progress of III-V nanotechnology, the present III-V heterostructure microelectronics will turn into what one might call III-V heterostructure nanoelectronics, and may open up a new future in much wider application areas than today, combining information technology, nanotechnology and biotechnology. Instead of the traditional top-down approach, new III-V heterostructure nanoelectronics will be formed on nanostructure networks formed by combination of top-down and bottom-up approaches. In addition to communication devices, emerging devices include high speed digital LSIs, various sensors, various smart-chips, quantum LSIs and quantum computation devices covering varieties of application areas. Ultra-low power quantum LSIs may become brains of smart chips and other nano-space systems. Achievements of new functions and higher performances and their on chip integration are key issues. Key processing issue remains to be understanding and control of nanostructure surfaces and interfaces in atomic scale.

In this paper, we study how a multidimensional local binary pattern (LBP) texture feature data can be visually explored and analyzed. The goal is to determine how true paper properties can be characterized with local texture features from visible light images. We utilize isometric feature mapping (Isomap) for the LBP texture feature data and perform non-linear dimensionality reduction for the data. These 2D projections are then visualized with original images to study data properties. Visualization is utilized in the manner of selecting texture models for unlabeled data and analyzing feature performance when building a training set for a classifier. The approach is experimented on with simulated image data illustrating different paper properties and on-line transilluminated paper images taken from a running paper web in the paper mill. The simulated image set is used to acquire quantitative figures on the performance while the analysis of real-world data is an example of semi-supervised learning.

An HEMT CCD (charge-coupled-device) matched filter for spread-spectrum communication was developed. For higher data rates, it was fabricated using a two-phase CCD based on HEMT technology. It operates at 1.6 GHz, and its calculated data rate is 100 Mbps with a PN data length of 16 bits (PN data rate is 1.6 GHz). And it attains a charge transfer efficiency (CTE) of 0.975 at 2 GHz. The HEMT CCD matched filter dissipates 173 mW from a 10-Vp-p supply, and its chip size is 0.961.03 mm. It will thus be useful for optical communication and other high-data-rate applications utilizing spread-spectrum (SS) communication.

In this paper, the confinement loss of octagonal photonic crystal fibers (PCFs) with an isosceles triangle lattice of air-holes are numerically investigated. Taking into account the confinement loss, the mode field diameter (MFD), the effective area (Aeff) and the chromatic dispersion of octagonal PCFs are calculated, compared to conventional hexagonal PCFs. It is found from confinement loss and MFD results that the octagonal PCFs can confine the field strongly than the hexagonal PCFs due to the different air filling fraction. Moreover, it is shown that the octagonal PCFs are obtained not only positive but also negative larger dispersion values and smaller Aeff values compared to the hexagonal PCFs.

An unsupervised adaptive signal processing method of principal components analysis (PCA) neural networks (NN) based on signal eigen-analysis is proposed to permit the eigenstructure analysis of lower signal to noise ratios (SNR) direct sequence spread spectrum (DS) signals. The objective of eigenstructure analysis is to estimate the pseudo noise (PN) of DS signals blindly. The received signal is firstly sampled and divided into non-overlapping signal vectors according to a temporal window, which duration is two periods of PN sequence. Then an autocorrelation matrix is computed and accumulated by these signal vectors one by one. Lastly, the PN sequence can be estimated by the principal eigenvector of autocorrelation matrix. Since the duration of temporal window is two periods of PN sequence, the PN sequence can be reconstructed by the first principal eigenvector only. Additionally, the eigen-analysis method becomes inefficient when the estimated PN sequence is long. We can use an unsupervised adaptive method of PCA NN to realize the PN sequence estimation from lower SNR input DS-SS signals effectively.

A spread-spectrum clock generator (SSCG) using fractional-N phase-locked loop (PLL) with an extended range sigma-delta (ΣΔ) modulator is presented in this paper. The proposed ΣΔ modulator simply adds an extra output bit in the first stage modulator. It can enlarge the input range about three times as compared to the conventional modulator and solve the saturation problem when the input exceeds the boundary of the conventional modulator. A flexible digital modulation controller can generate center and down spread-spectrum modulation and each has spread ratios of 0.4%, 0.8%, 1.6% and 3.2%. The proposed SSCG has been fabricated in TSMC 0.35-µm double-poly quadruple-metal CMOS process with output frequency of 300 MHz. The active area is 0.630.62 mm2 and the power consumption is 17.5 mW.

In this paper, we propose a combination-based novel technique of dithered subband coding with spectral subtraction for improving the perceptual quality of coded audio at low bit rates. It is well known that signal-correlated distortion is audible when the audio signal is quantized at bit rates lower than the lower bound of perceptual coding. We show that this problem can be overcome by applying the dithering quantization process in each subband. Consequently, the quantization noise is rendered into a signal-independent white noise; this noise is then estimated and removed by spectral subtraction at the decoder. Experimental results show an effective improvement by the proposed method over the conventional one in terms of better SNR and human listening test results. The proposed method can be combined with other existing or future coding methods such as perceptual coding to improve their performance at low bit rates.