In this paper, we discuss the relationship between the test generation complexity for path delay faults (PDFs) and that for stuck-at faults (SAFs) in combinational and sequential circuits using the recently introduced τk-notation. On the other hand, we also introduce a class of cyclic sequential circuits that are easily testable, namely two-column distributive state-shiftable finite state machine realizations (2CD-SSFSM). Then, we discuss the relevant conjectures and unsolved problems related to the test generation for sequential circuits with PDFs under different clock schemes and test generation models.

Existing methods for inverse motion compensation (IMC) in the DCT domain have not considered the unrestricted motion vector (UMV). In the existing methods, IMC is performed to deal with the UMV in the spatial domain after the inverse DCT (IDCT). We propose an IMC method which can deal with the UMV directly in the DCT domain without the use of the IDCT/DCT required by the existing methods. The computational complexity of the proposed method can be reduced by about half of that of the brute-force method operating in the spatial domain. Experimental results show that the proposed method can efficiently reduce the processing time with similar visual quality.

This paper proposes probabilistic pruning techniques for a Bayesian video face recognition system. The system selects the most probable face model using model posterior distributions, which can be calculated using a Sequential Monte Carlo (SMC) method. A combination of two new pruning schemes at the resampling stage significantly boosts computational efficiency by comparison with the original online learning algorithm. Experimental results demonstrate that this approach achieves better performance in terms of both processing time and ID error rate than a contrasting approach with a temporal decay scheme.

In this paper, we propose one low-computation cycle and power-efficient recursive discrete Fourier transform (DFT)/inverse DFT (IDFT) architecture adopting a hybrid of input strength reduction, the Chebyshev polynomial, and register-splitting schemes. Comparing with the existing recursive DFT/IDFT architectures, the proposed recursive architecture achieves a reduction in computation-cycle by half. Appling this novel low-computation cycle architecture, we could double the throughput rate and the channel density without increasing the operating frequency for the dual tone multi-frequency (DTMF) detector in the high channel density voice over packet (VoP) application. From the chip implementation results, the proposed architecture is capable of processing over 128 channels and each channel consumes 9.77 µW under 1.2 V@20 MHz in TSMC 0.13 1P8M CMOS process. The proposed VLSI implementation shows the power-efficient advantage by the low-computation cycle architecture.

A reversible data hiding scheme based on the companding technique and the difference expansion (DE) of triplets is proposed in this paper. The companding technique is employed to increase the number of the expandable triplets. The capacity consumed by the location map recording the expanded positions is largely decreased. As a result, the hiding capacity is considerably increased. The experimental results reveal that high hiding capacity can be achieved at low embedding distortion.

This paper proposes a new computational optimization method modified from the dynamic encoding algorithm for searches (DEAS). Despite the successful optimization performance of DEAS for both benchmark functions and parameter identification, the problem of exponential computation time becomes serious as problem dimension increases. The proposed optimization method named univariate DEAS (uDEAS) is especially implemented to reduce the computation time using a univariate local search scheme. To verify the algorithmic feasibility for global optimization, several test functions are optimized as benchmark. Despite the simpler structure and shorter code length, function optimization performance show that uDEAS is capable of fast and reliable global search for even high dimensional problems.

This paper proposes a novel robust fundamental frequency (F0) estimation algorithm based on complex-valued speech analysis for an analytic speech signal. Since analytic signal provides spectra only over positive frequencies, spectra can be accurately estimated in low frequencies. Consequently, it is considered that F0 estimation using the residual signal extracted by complex-valued speech analysis can perform better for F0 estimation than that for the residual signal extracted by conventional real-valued LPC analysis. In this paper, the autocorrelation function weighted by AMDF is adopted for the F0 estimation criterion and four signals; speech signal, analytic speech signal, LPC residual and complex LPC residual, are evaluated for the F0 estimation. Speech signals used in the experiments were an IRS filtered speech corrupted by adding white Gaussian noise or Pink noise whose noise levels are 10, 5, 0, -5 [dB]. The experimental results demonstrate that the proposed algorithm based on complex LPC residual can perform better than other methods in noisy environment.

This paper proposes a new adaptive filter algorithm for system identification by using an independent component analysis (ICA) technique, which separates the signal from noisy observation under the assumption that the signal and noise are independent. We first introduce an augmented state-space expression of the observed signal, representing the problem in terms of ICA. By using a nonparametric Parzen window density estimator and the stochastic information gradient, we derive an adaptive algorithm to separate the noise from the signal. The proposed ICA-based algorithm does not suppress the noise in the least mean square sense but to maximize the independence between the signal part and the noise. The computational complexity of the proposed algorithm is compared with that of the standard NLMS algorithm. The stationary point of the proposed algorithm is analyzed by using an averaging method. We can directly use the new ICA-based algorithm in an acoustic echo canceller without double-talk detector. Some simulation results are carried out to show the superiority of our ICA method to the conventional NLMS algorithm.

Digital hearing aid users often complain of difficulty in understanding speech in the presence of background noise. To improve speech perception in a noisy environment, various speech enhancement algorithms have been applied in digital hearing aids. In this study, a speech enhancement algorithm using modified spectral subtraction and companding is proposed for digital hearing aids. We adjusted the biases of the estimated noise spectrum, based on a subtraction factor, to decrease the residual noise. Companding was applied to the channel of the formant frequency based on the speech presence indicator to enhance the formant. Noise suppression was achieved while retaining weak speech components and avoiding the residual noise phenomena. Objective and subjective evaluation under various environmental conditions confirmed the improvement due to the proposed algorithm. We tested segmental SNR and Log Likelihood Ratio (LLR), which have higher correlation with subjective measures. Segmental SNR has the highest and LLR the lowest correlation of the methods tested. In addition, we confirmed by spectrogram that the proposed method significantly reduced the residual noise and enhanced the formants. A mean opinion score that represented the global perception score was tested; this produced the highest quality speech using the proposed method. The results show that the proposed speech enhancement algorithm is beneficial for hearing aid users in noisy environments.

Implementing the fast-responding multi-layer service network (MLSN) functionality will allow the IP/MPLS service network logical topology and Optical Virtual Network topology to be reconfigured dynamically according to the traffic pattern on the network. Direct links can be created or removed in the logical IP/MPLS service network topology, when either extra capacity in MLSN core is needed or existing capacity in core is no longer required. Reconfiguring the logical and virtual network topologies constitute a new manner by which Traffic Engineering (TE) can solve or avoid network congestion problems and service degradations. As both IP and optical network layers are involved, this is called Multi-layer Traffic Engineering. We proposed border model based MLSN architecture in [5]. In this paper, we define the realization of Multi-Layer TE functions using Path Computation Element (PCE) for Border model based MLSN. It defines nodal requirements for multi-layer TE. Requirements of communication protocol between PCC (Path Computation Client) and PCE is introduced. It presents Virtual Network Topology (VNT) scenarios and steps involved along with examples for PCE-based VNT reconfiguration triggered by network failure, where VNT is a set of different layer's network resource accumulation.

The key weakness of Low-Density Parity Check codes is the complexity of the encoding scheme. The generator matrices can be made by Gaussian elimination of parity check matrices for normal block codes. Richardson succeeded in making parity bits from parity check matrices by the low density computation. In this letter, we focus on the execution of numerical experiments which show that even if the matrix D, which is the part of the Richardson's LDPC matrix, is restricted, proposed LDPC codes is lower complexity than Richardson's LDPC codes. The constraint of D results in reducing complexity from O(n + g2) to O(n) due to the omission of computing inverse matrices of φ and T in Richardson's encoding scheme. All the sub-matrices in parity check matrix are composed of Circulant Permutation Matrices based on Galois Fields.

This paper considers reduction of the peak-to-average power ratio (PAPR) of M-quadrature amplitude modulation (QAM) signals in orthogonal frequency division multiplexing (OFDM) systems. It is known that a 16-QAM or 64-QAM constellation can be written as the vector sum of two or three QPSK constellations respectively. We can then use the Golay complementary sequences over Z4 to construct 16-QAM or 64-QAM OFDM sequences with low PAPR. In this paper, we further examine the squared Euclidean distance of these M-QAM sequences and their variations. Our goal here is to combine the block coded modulation (BCM) and Golay complementary sequences to trade off the PAPR, the code rate, and the squared Euclidean distance of M-QAM OFDM signals. In particular, some 16-QAM and 64-QAM OFDM sequences with low PAPR and large squared Euclidean distance are presented.

This study investigates a new transmission method of light from a point source in a multimode graded-index fiber. The position of the point source is arranged along with a mode pattern to precisely determine the location of an output point image. Propagation performance is observed in an experiment and estimated by simulation.

Internet access traffic follows hourly patterns that depend on various factors, such as the periods users stay on-line at the access point (e.g. at home or in the office) or their preferences for applications. The clustering of Internet users may provide important information for traffic engineering and billing. For example, it can be used to set up service differentiation according to hourly behavior, resource optimization based on multi-hour routing and definition of tariffs that promote Internet access in low busy hours. In this work, we propose a methodology for clustering Internet users with similar patterns of Internet utilization, according to their hourly traffic utilization. The methodology resorts to three statistical multivariate analysis techniques: cluster analysis, principal component analysis and discriminant analysis. The methodology is illustrated through measured data from two distinct ISPs, one using a CATV access network and the other an ADSL one, offering distinct traffic contracts. Principal component analysis is used as an exploratory tool. Cluster analysis is used to identify the relevant Internet usage profiles, with the partitioning around medoids and Ward's method being the preferred clustering methods. For the two data sets, these methods lead to the choice of 3 clusters with different hourly traffic utilization profiles. The cluster structure is validated through discriminant analysis. It is also evaluated in terms of several characteristics of the user traffic not used in the cluster analysis, such as the type of applications, the amount of downloaded traffic, the activity duration and the transfer rate, resulting in coherent outcomes.

This paper deals with adaptive array beamforming based on stochastic gradient descent independent component analysis (ICA) for suppressing interference with robust capabilities. The approach first uses estimates of the interested source directions to construct the multiple regularized constraints, which form an efficient ICA-based beamformer to achieve fast convergence and more robust capabilities than existing MCMV and ESB beamformers. In conjunction with the regularization parameters of the high-order derivative constraints, the width of the main beam for remaining the desired signal and the depth of nulls for suppressing interferers can be adjusted. Several computer simulation examples are provided for illustration and comparison.

NEXT (Near End Crosstalk loss) and FEXT (Far End Crosstalk loss) of a high speed LAN connector are analyzed using a simple coupled line model and examined experimentally. "Crosstalk Chart" is also proposed, by which, the NEXT and FEXT can be easily read off from the mutual inductance and unbalanced capacitance between pair of lines. This approach is effective for Cat.5e [1] connectors. However, for Cat.6 [2], of which transmission bandwidth is widen to 250 MHz, some additional adjustments of path pattern on the jack and terminals PCB are required. In order to assist such the adjustments, a new simple measurement technique to grasp the complex crosstalk characteristics is proposed. Two examples are introduced. One is a conventional telephone rosette, which is enhanced to be co-usable for a Cat.5e LAN connector, where only its original circuit board is reengineered. Another is a Cat.6 connector of which PCB is modified from a conventional Cat.5e connector.

A communication means is presented for patients with amyotrophic lateral sclerosis in totally locked-in state who are completely unable to move any part of the body and have no usual communication means. The method utilizes changes in cerebral blood volume accompanied with changes in brain activity. When a patient is asked a question and the answer to it is 'yes', the patient makes his or her brain active. The change in blood volume at the frontal lobe is detected with near-infrared light. The instantaneous amplitude and phase of the change are calculated, and the maximum amplitude and phase change are obtained. The answer 'yes' or 'no' of the patient is detected using a discriminant analysis with these two quantities as variables. The rate of correct detection is 80% on average.

An adaptive subcarrier allocation (SA) algorithm is proposed for both the enhancement of system capacity and the practical implementation in a clustered OFDM system. The proposed algorithm is based on the two dimensional comparison of the channel gain in both rows and columns of the channel matrix to achieve higher system capacity. Simulation results demonstrate that the proposed algorithm outperforms the SA algorithm based on only one dimensional comparison in terms of system capacity, and furthermore, it performs as well as the optimal SA algorithm at relatively low computational cost.

The possibility of using three kinds of new type composite materials as material for high speed sliding contacts was investigated. The results of this investigation were compared with the results of the low speed tests that were reported earlier. As a result of the above, it was discovered that for high speed rotation in the range from 0.014 m/s to 2 m/s, the order of merit did not significantly change. Based on this, it was concluded that if solid lubricant is effectively supplied to the sliding surface, the influence by frictional heat generated by high speed is slight. Of the three kinds of composite material, it was clarified that composite material (CMML-1) had the lowest contact resistance and Composite Material (CMML-3) had the lowest maximum frictional coefficient of friction. 'CM' and 'ML' are initialisms for 'Composite Material' and 'Material of Lubrication' respectively. The number that is attached to the material name is a numeric value that was set by this laboratory.

This paper presents a novel feature extraction algorithm based on particle swarms for processing hyperspectral imagery data. Particle swarm optimization, originally developed for global optimization over continuous spaces, is extended to deal with the problem of feature extraction. A formulation utilizing two swarms of particles was developed to optimize simultaneously a desired performance criterion and the number of selected features. Candidate feature sets were evaluated on a regression problem. Artificial neural networks were trained to construct linear and nonlinear models of chemical concentration of glucose in soybean crops. Experimental results utilizing real-world hyperspectral datasets demonstrate the viability of the method. The particle swarms-based approach presented superior performance in comparison with conventional feature extraction methods, on both linear and nonlinear models.