Internet group-based application layer services such as the overlay networks and P2P systems can benefit from end-to-end network status information. An efficient and accurate bandwidth measurement technique plays an important role in acquiring this information. We propose an end-to-end bottleneck link capacity measurement technique that utilizes path signatures combined with graphical analyses. This feature reduces the probe overhead and decreases the convergence time. We used ns-2 simulations and actual Internet measurements, which resulted in a high level of accuracy and a short probe time with low overhead.

The performance of spectrum sensing in cognitive radio can be improved by employing multiple antennas. In this letter, the effect of antenna correlation on the performance improvement by deploying multiple antennas in the sensing node of the secondary system is investigated. It is proved mathematically that in the regime of low SNR, with antenna correlation, the secondary sensing node can achieve almost the same performance improvement as that without correlation. Simulation results verify the conclusions.

We propose a low-memory-bandwidth, high-efficiency VLSI architecture for 60-k word real-time continuous speech recognition. Our architecture includes a cache architecture using the locality of speech recognition, beam pruning using a dynamic threshold, two-stage language model searching, a parallel Gaussian Mixture Model (GMM) architecture based on the mixture level and frame level, a parallel Viterbi architecture, and pipeline operation between Viterbi transition and GMM processing. Results show that our architecture achieves 88.24% required frequency reduction (66.74 MHz) and 84.04% memory bandwidth reduction (549.91 MB/s) for real-time 60-k word continuous speech recognition.

Mobile operators need to migrate from 2G to 3G networks in a cost-effective manner. Cognitive radio systems are currently being investigated as a promising solution to achieve spectrum efficiency by allowing coexistence of unlicensed (secondary) networks and licensed (primary) networks. However, conventional mechanisms to operate these systems incur additional complexity and fail to maximize network performance. In this paper, we propose a pilot sensing and frequency selection method with low complexity for OFDMA-based cognitive radio systems. Subject to the interference constraints imposed by the primary network, capacity maximization problems involving both up-link and down-link connections are considered for overall network performance improvement. The throughput and outage probability of the proposed method are evaluated by simulations. Our proposed method shows outstanding performance if the channel varies frequently in the primary network and the frequency reuse factor of the primary network is high.

The extended binary phase shift keying (EBPSK) transmission system with ultra narrow bandwidth has excellent BER performance, which raises many doubts with the researchers. Therefore, on the premise of the existence of a special filter that can transform the modulated phase information into amplitude information, the theoretical BER formula of EBPSK system in Additive White Gaussian Noise (AWGN) channel has been deduced. This paper gives the theoretical values of the parameters in the above BER formula and discusses the effects of parameters on BER firstly. Then the paper shows that the special impacting filter satisfies the above assumption, therefore, in the frame of binary detection theory, the excellent performance of high-efficiency EBPSK system can be explained and the correction of the theoretical BER formula can be validated.

We propose a blind dereverberation method based on spectral subtraction using a multi-channel least mean squares (MCLMS) algorithm for distant-talking speech recognition. In a distant-talking environment, the channel impulse response is longer than the short-term spectral analysis window. By treating the late reverberation as additive noise, a noise reduction technique based on spectral subtraction was proposed to estimate the power spectrum of the clean speech using power spectra of the distorted speech and the unknown impulse responses. To estimate the power spectra of the impulse responses, a variable step-size unconstrained MCLMS (VSS-UMCLMS) algorithm for identifying the impulse responses in a time domain is extended to a frequency domain. To reduce the effect of the estimation error of the channel impulse response, we normalize the early reverberation by cepstral mean normalization (CMN) instead of spectral subtraction using the estimated impulse response. Furthermore, our proposed method is combined with conventional delay-and-sum beamforming. We conducted recognition experiments on a distorted speech signal simulated by convolving multi-channel impulse responses with clean speech. The proposed method achieved a relative error reduction rate of 22.4% in relation to conventional CMN. By combining the proposed method with beamforming, a relative error reduction rate of 24.5% in relation to the conventional CMN with beamforming was achieved using only an isolated word (with duration of about 0.6 s) to estimate the spectrum of the impulse response.

In this letter, we give a generalized construction for sets of frequency-hopping sequences (FHSs) based on power-residue sequences. Our construction encompasses a known optimal construction and can generate new optimal sets of FHSs which simultaneously achieve the Peng-Fan bound and the Lempel-Greenberger bound.

This paper proposes Bayesian context clustering using cross validation for hidden Markov model (HMM) based speech recognition. The Bayesian approach is a statistical technique for estimating reliable predictive distributions by treating model parameters as random variables. The variational Bayesian method, which is widely used as an efficient approximation of the Bayesian approach, has been applied to HMM-based speech recognition, and it shows good performance. Moreover, the Bayesian approach can select an appropriate model structure while taking account of the amount of training data. Since prior distributions which represent prior information about model parameters affect estimation of the posterior distributions and selection of model structure (e.g., decision tree based context clustering), the determination of prior distributions is an important problem. However, it has not been thoroughly investigated in speech recognition, and the determination technique of prior distributions has not performed well. The proposed method can determine reliable prior distributions without any tuning parameters and select an appropriate model structure while taking account of the amount of training data. Continuous phoneme recognition experiments show that the proposed method achieved a higher performance than the conventional methods.

A new type of modulation called continuous-phase parallel-combinatory high-compaction multicarrier modulation (CPPC/HC-MCM) is proposed. CPPC/HC-MCM employs the technique of continuous-phase modulation (CPM) and avoids the formation of amplitude gaps between two successive signals to enhance the spectral efficiency of conventional PC/HC-MCM. Results of simulations show that CPPC/HC-MCM is spectrally efficient and achieves a smaller bit error rate than conventional (unmodulated) PC/HC-MCM at a common spectral efficiency even if the peak-to-average power ratio is considered.

In this letter, we analyze the effect of the size of observed data on the performance of time delay estimation (TDE) in the chirp spread spectrum (CSS) system. By adjusting the size of observed data, we reduce the effect of DC offsets, which would otherwise degrade the performance of TDE based on CSS, and we optimize the performance of TDE in CSS system. Finally, we derive the optimal size of observed data of TDE in CSS system.

This study focuses on speaker adaptation techniques for Computer-Assisted Language Learning (CALL). We first investigate the effects and problems of Maximum Likelihood Linear Regression (MLLR) speaker adaptation when used in pronunciation evaluation. Automatic scoring and error detection experiments are conducted on two publicly available databases of Japanese learners' English pronunciation. As we expected, over-adaptation causes misjudgment of pronunciation accuracy. Following the analysis, we propose a novel method, Regularized Maximum Likelihood Regression (Regularized-MLLR) adaptation, to solve the problem of the adverse effects of MLLR adaptation. This method uses a group of teachers' data to regularize learners' transformation matrices so that erroneous pronunciations will not be erroneously transformed as correct ones. We implement this idea in two ways: one is using the average of the teachers' transformation matrices as a constraint to MLLR, and the other is using linear combinations of the teachers' matrices to represent learners' transformations. Experimental results show that the proposed methods can better utilize MLLR adaptation and avoid over-adaptation.

The purpose of this work is to synthesize a three-dimension C60 polymer using photo-polymerization method. The used pristine materials were C60 precipitates prepared by a liquid-liquid interfacial precipitation (LLIP) method. The prepared LLIP material was set in the vacuum and was compressed in the anvil with the pressure of 600 MPa or 7 GPa. The 4th harmonics FEL with the wavelength of 500 nm was irradiated with macro-pulses (the pulse width of 20 µs) containing very short micro-pulses (the pulse width of 200 fs). The Raman Ag(2) peak of C60 molecules in the vicinity of 1469 cm-1 becomes broad and shifts to the lower energy region as proceeding of polymerization. Under high pressure and/or FEL irradiation the LLIP crystal revealed the large red-shift and the increment of the half width of the Raman Ag(2) peak. Furthermore the LLIP crystal mixture with iodine revealed the more distinctive red-shift, ca.13cm-1 because of highly packing of C60 molecules. The C60 molecular accession by LLIP process and/or the photo-assisted hole-doping from iodine were promising conditions to promote the photo-polymerization effectively.

To meet the increasing demand to expand wavelength division multiplexing (WDM) transmission capacity, ultrahigh spectral density coherent optical transmission employing multi-level modulation formats has attracted a lot of attention. In particular, ultrahigh multi-level quadrature amplitude modulation (QAM) has an enormous advantage as regards expanding the spectral efficiency to 10 bit/s/Hz and even approaching the Shannon limit. We describe fundamental technologies for ultrahigh spectral density coherent QAM transmission and present experimental results on polarization-multiplexed 256 QAM coherent optical transmission using heterodyne and homodyne detection with a frequency-stabilized laser and an optical phase-locked loop technique. In this experiment, Raman amplifiers are newly adopted to decrease the signal power, which can reduce the fiber nonlinearity. As a result, the power penalty was reduced from 5.3 to 2.0 dB. A 64 Gbit/s data signal is successfully transmitted over 160 km with an optical bandwidth of 5.4 GHz.

In situ observation of the adsorption process and the states of cytochrome c on glass/solution interfaces, and the functionality of the reduction reaction of adsorbed cytochorome c were performed by using slab optical waveguide (SOWG) spectroscopy. The peak position of the absorption band of cytochorome c adsorbed on a bare glass surface was almost the same as that of that in solution. The cytochorome c adsorbed on glass/solution interface was reduced by sodium dithionite solution. The adsorbed cytochorome c was still maintained its functionality after immobilization.

In this letter, the compensation ability of nonlinear distortions for loudspeaker systems is demonstrated using dynamic distortion measurement. Two linearization methods using a Volterra filter and a Mirror filter are compared. The conventional evaluation utilizes swept multi-sinusoidal waves. However, it is unsatisfactory because wideband signals such as those of music and voices are usually applied to loudspeaker systems. Hence, the authours use dynamic distortion measurement employing a white noise. Experimental results show that the two linearization methods can effectively reduce nonlinear distortions for wideband signals.

The nanoporosity installed in conjugated polymer films prepared by electrophoretic deposition makes it difficult to measure the amount of polymer deposited on a substrate. Here, an alternative approach, the estimation of material efficiency of the electrophoretic deposition from the optical absorption spectra of the residual suspensions has been studied. The ultimate recovery rate, which becomes smaller in suspensions with lower acetonitrile content, does not depend on the deposition voltage. The light scattering by the colloidal particles seems to be absent in residual suspensions after a deposition long enough to reach the ultimate recovery rate, indicating the exhaustion of the colloidal particles. Although the deposition rate of the polymer markedly lowers upon coating of the deposition electrode with PEDOT, the ultimate recovery rate remains unchanged. These results suggest that the material efficiency in this deposition method is limited by the generation rate of the colloidal particles in the suspension.

High luminance and high speed response with the cut-off frequency of more than 50 MHz in multilayer polyfluorene-based light-emitting diodes with an interlayer were achieved. We realized multilayer polyfluorene-based light-emitting diodes for frequency response up to 100 MHz.

We demonstrate a single-channel 1.28 Tbit/s-525 km transmission using OTDM of subpicosecond DQPSK signals. In order to cope with transmission impairments due to time-varying higher-order PMD, which is one of the major limiting factors in such a long-haul ultrahigh-speed transmission, we newly developed an ultrafast time-domain optical Fourier transformation technique in a round-trip configuration. By applying this technique to subpicosecond pulses, transmission impairments were greatly reduced, and BER performance below FEC limit was obtained with increased system margin.

The traditional spectrum auctions require a central auctioneer. Then, the secondary users (SUs) can bid for spectrum in multiple auction or sealed auction way. In this paper, we address the problem of distributed spectrum sharing in the cognitive networks where multiple owners sell their spare bands to multiple SUs. Each SU equips multi-interface/multi-radio, so that SU can buy spare bands from multiple owners. On the other hand, each owner can sell its spare bands to serval SUs. There are two questions to be addressed for such an environment: the first one is how to select bands/the owners for each SU; the second one is how to decide the competitive prices for the multiple owners and multiple SUs. To this end, we propose a two-side multi-band market game theoretic framework to jointly consider the benefits of all SUs and owners. The equilibrium concept in such games is named core. The outcomes in the core of the game cannot be improved upon by any subset of players. These outcomes correspond exactly to the price-lists that competitively balance the benefits of all SUs and owners. We show that the core in our model is always non-empty. When the measurement of price takes discrete value, the core of the game is defined as discrete core. The Dynamic Multi-band Sharing algorithm (DMS) is proposed to converge to the discrete core of the game. With small enough measurement unit of price, the algorithm can achieve the optimal performance compared with centralized one in terms of the system utility.

We review our recent work on ultra-long-haul wavelength division multiplexed (WDM) transmission with high spectral efficiency (SE) employing tight pre-filtering and multi-symbol detection. We start the discussion with a theoretical evaluation of the SE limit of pre-filtered modulation in optical fiber communication systems. We show that pre-filtering induced symbol correlation generates a modulation with memory and thus, a higher SE limit than that of the original memory-less modulation. We also investigate the merits of utilizing the pre-filtering induced symbol correlation with multi-symbol detection to achieve high SE transmission. We demonstrate transoceanic WDM transmission of a pre-filtered polarization division multiplexed return-to-zero quaternary phased shift keying (PDM-RZ-QPSK) modulation format with multi-symbol detection, achieving 419% SE which is higher than the SE limit of the original memory-less PDM-RZ-QPSK format.