Acoustic feature transformation is widely used to reduce dimensionality and improve speech recognition performance. In this letter we focus on dimensionality reduction methods that minimize the average classification error. Unfortunately, minimization of the average classification error may cause considerable overlaps between distributions of some classes. To mitigate risks of considerable overlaps, we propose a dimensionality reduction method that minimizes the maximum classification error. We also propose two interpolated methods that can describe the average and maximum classification errors. Experimental results show that these proposed methods improve speech recognition performance.

Capture-safety, (defined as the avoidance of timing error due to unduly high launch switching activity in capture mode during at-speed scan testing), is critical in avoiding test induced yield loss. Although several sophisticated techniques are available for reducing capture IR-drop, there are few complete capture-safe test generation flows. This paper addresses the problem by proposing a novel and practical capture-safe test generation flow, featuring (1) a complete capture-safe test generation flow; (2) reliable capture-safety checking; and (3) effective capture-safety improvement by combining X-bit identification & X-filling with low launch-switching-activity test generation. The proposed flow minimizes test data inflation and is compatible with existing automatic test pattern generation (ATPG) flow. The techniques proposed in the flow achieve capture-safety without changing the circuit-under-test or the clocking scheme.

In this paper, we propose a novel data hiding technique for G.711-coded speech based on the LSB substitution method. The novel feature of the proposed method is that a low-bitrate encoder, G.726 ADPCM, is used as a reference for deciding how many bits can be embedded in a sample. Experiments showed that the method outperformed the simple LSB substitution method and the selective embedding method proposed by Aoki. We achieved 4-kbit/s embedding with almost no subjective degradation of speech quality, and 10 kbit/s while maintaining good quality.

Error-propagation is an important issue and should be carefully coped with in the decision-feedback equalizers (DFE). Ignoring the impact of error-propagation often leads to impractical laboratory results. In this paper, we investigate two novel layered space-frequency equalizers (LSFE) for single-carrier multiple-input multiple-output (MIMO) systems, where the recently proposed frequency-domain equalizer with time domain noise-predictor (FDE-NP) is adopted at each stage of the LSFE. We first derive the partially-connected LSFE with noise predictor (PC-LSFE-NP) which has exactly the same mean square error (MSE) as the conventional LSFE under the assumption of perfect feedback. However, if error-propagation is considered, the proposed PC-LSFE-NP can achieve better performance than the conventional LSFE due to the more reliable feedback output by the decoders. To reduce the interference from the not yet detected layers in the feedback section, we then introduce the fully-connected LSFE with noise predictor (FC-LSFE-NP), in which all layers are implicitly equalized within each stage and their decisions fed back internally. The powerful feedback filter of FC-LSFE-NP brings significant performance superiority over the conventional LSFE and PC-LSFE-NP with either perfect or imperfect feedback. Moreover, we propose a simple soft-demapper for the equalizers to avoid information loss during decoding, and thus, further improve the performance. Finally, we compare the performance of (PC/FC)-LSFE-NP with the existing schemes by computer simulations.

We investigated the effect of a high-speed power line communication (PLC) signal induced into a very high-speed digital subscriber line (VDSL) system by conductive coupling based on a network model. Four electronic devices with AC mains and telecommunication ports were modeled using a 4-port network, and the parameters of the network were obtained from measuring impedance and transmission loss. We evaluated the decoupling factor from the mains port to the telecommunication port of a VDSL modem using these parameters for the four electric and electronic devices. The results indicate that the mean value of the decoupling factor for the differential and common mode signals were more than 88 and 62 dB, respectively, in the frequency range of a PLC system. Taking the following parameters into consideration; decoupling factor Ld, the average transmission signal powers of VDSL and PLC, desired and undesired (DU) ratio, and transmission loss of a typical 300-m-long indoor telecommunication line, the VDSL system cannot be disturbed by the PLC signal induced into the VDSL modem from the AC mains port in normal installation.

This paper considers an optimized limited feedback design for a multi-antenna system serving multiple users under different types of channels: Rayleigh distributed and line-of-sight distributed channels. Since the users are asymmetric, we propose an optimized feedback bandwidth allocation scheme for users under a total feedback rate constraint. The allocation scheme is designed according to the long-term channel type information of users, and thus it can be efficiently implemented. Numerical results verify the effectiveness of our proposed scheme.

This letter proposes a new practical multiuser MIMO (MU-MIMO) scheme, which is an evolution of the well-known Per User Unitary beamforming Rate Control (PU2RC) proposed for 3GPP-LTE and IEEE802.16m standards. The proposed scheme includes an efficient user scheduling algorithm which alleviates the major weakness of the conventional PU2RC. Numerical results show that the proposed scheme provides notable performance improvement especially with small and medium user pool since it effectively exploits the benefit from large codebook size.

This paper proposes a pattern partitioning algorithm that maps multiple target patterns onto homogeneous memory-based string matchers. The proposed algorithm adopts the greedy search based on lexicographical sorting. By mapping as many target patterns as possible onto each string matcher, the memory requirements are greatly reduced.

The planar Hajos calculus (PHC) is the Hajos calculus with the restriction that all the graphs that appear in the construction (including a final graph) must be planar. The degree-d planar Hajos calculus (PHC(dd)) is PHC with the restriction that all the graphs that appear in the construction (including a final graph) must have maximum degree at most d. We prove the followings: (1) If PHC is polynomially bounded, then for any d ≥ 4, PHC(dd+2) can generate any non-3-colorable planar graphs of maximum degree at most d in polynomial steps. (2) If PHC can generate any non-3-colorable planar graphs of maximum degree 4 in polynomial steps, then PHC is polynomially bounded.

Feedback shift registers are basic building blocks for many cryptographic primitives. Due to the insecurities of Linear Feedback Shift Register (LFSR) based systems, the use of Nonlinear Feedback Shift Registers (NFSRs) became more popular. In this work, we study the feedback functions of NFSRs with period 2n. First, we provide two new necessary conditions for feedback functions to be maximum length. Then, we consider NFSRs with k-monomial feedback functions and focus on two extreme cases where k=4 and k=2n-1. We study construction methods for these special cases.

In this paper, we describe a novel model training method for one-to-many eigenvoice conversion (EVC). One-to-many EVC is a technique for converting a specific source speaker's voice into an arbitrary target speaker's voice. An eigenvoice Gaussian mixture model (EV-GMM) is trained in advance using multiple parallel data sets consisting of utterance-pairs of the source speaker and many pre-stored target speakers. The EV-GMM can be adapted to new target speakers using only a few of their arbitrary utterances by estimating a small number of adaptive parameters. In the adaptation process, several parameters of the EV-GMM to be fixed for different target speakers strongly affect the conversion performance of the adapted model. In order to improve the conversion performance in one-to-many EVC, we propose an adaptive training method of the EV-GMM. In the proposed training method, both the fixed parameters and the adaptive parameters are optimized by maximizing a total likelihood function of the EV-GMMs adapted to individual pre-stored target speakers. We conducted objective and subjective evaluations to demonstrate the effectiveness of the proposed training method. The experimental results show that the proposed adaptive training yields significant quality improvements in the converted speech.

As the spread of high-speed networks and the development of network technologies, P2P technologies are actively used today for information exchange in the network. While information exchange in a P2P network is quite flexible, there is an important problem--lack of reliability. Since we cannot know the details of how the data was obtained, it is hard to fully rely on it. To ensure the reliability of exchanged data, we have proposed the framework of a traceable P2P record exchange based on database technologies. In this framework, records are exchanged among autonomous peers, and each peer stores its exchange and modification histories in it. The framework supports the function of tracing queries to query the details of the obtained data. A tracing query is described in datalog and executed as a recursive query in the P2P network. In this paper, we focus on the query processing strategies for the framework. We consider two types of queries, ad hoc queries and continual queries, and present the query processing strategies for their executions.

In this paper the SNR estimation is performed frame by frame, during the speech activity. For this purpose, the fourth-order moments of the real and imaginary parts of frequency components are extracted, for both the speech and noise, separately. For each noisy frame, the mentioned fourth-order moments are also estimated. Making use of the proposed formulas, the signal-to-noise ratio is estimated in each frequency index of the noisy frame. These formulas also predict the overall signal-to-noise ratio in each noisy frame. What makes our method outstanding compared to conventional approaches is that this method takes into consideration both the speech and noise identically. It estimates the negative SNR almost as well as the positive SNR.

We propose a moving picture coding by lapped transform and an edge adaptive deblocking filter to reduce the blocking distortion. We apply subband coding (SBC) with lapped transform (LT) and zero pruning set partitioning in hierarchical trees (zpSPIHT) to encode the difference picture. Effective coding using zpSPIHT was achieved by quantizing and pruning the quantized zeros. The blocking distortion caused by block motion compensated prediction is reduced by an edge adaptive deblocking filter. Since the original edges can be detected precisely at the reference picture, an edge adaptive deblocking filter on the predicted picture is very effective. Experimental results show that blocking distortion has been visually reduced at very low bit rate coding and better PSNRs of about 1.0 dB was achieved.

Free probability theory, which has become a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large matrices. In this paper, using asymptotic free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how the asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radio. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance than the energy detection techniques and the Maximum-minimum eigenvalue (MME) scheme even for the case of a small sample of observations.

This paper presents a CMOS signal detection circuit for 2.5 Gb/s serial data communication system over FR-4 backplane. This overcomes characteristics deviation of full-wave rectifier-based simple power detection circuits due to data pattern and temperature by using an edge detector and a sample-hold circuit.

In this paper, we propose a novel method based on the second-order conditional maximum a posteriori (CMAP) to improve the performance of the global soft decision in speech enhancement. The conventional global soft decision scheme is found through investigation to have a disadvantage in that the global speech absence probability (GSAP) in that scheme is adjusted by a fixed parameter, which could be a restrictive assumption in the consecutive occurrences of speech frames. To address this problem, we devise a method to incorporate the second-order CMAP in determining the GSAP, which is clearly different from the previous approach in that not only current observation but also the speech activity decisions of the previous two frames are exploited. Performances of the proposed method are evaluated by a number of tests in various environments and show better results than previous work.

This paper describes non-reference objective quality evaluation for noise-reduced speech. First, a subjective test is conducted in accordance with ITU-T Rec. P.835 to obtain the speech quality, the noise quality, and the overall quality of noise-reduced speech. Based on the results, we then propose an overall quality estimation model. The unique point of the proposed model is that the estimation of the overall quality is done only using the previously estimated speech quality and noise quality, in contrast to conventional models, which utilize the acoustical features extracted. Finally, we propose a non-reference objective quality evaluation method using the proposed model. The results of an experiment with different noise reduction algorithms and noise types confirmed that the proposed method gives more accurate estimates of the overall quality compared with the method described in ITU-T Rec. P.563.

This study focuses on system throughput by taking into account the channel interference in IEEE 802.15.3c WPAN, which is based on the hybrid multiple access of CSMA/CA and TDMA, namely CSMA/CA-TDMA. To study the system throughput, we construct a novel analytical model by taking into consideration the channel interference caused by the hidden networks in CSMA/CA-TDMA. The obtained results show that the system throughput achieved by TDMA is highly affected by frame transmission in CSMA/CA. Furthermore, we show that channel interference, which causes a degradation in the system throughput, is a very significant problem in the IEEE 802.15.3c WPAN.

In previous studies, the retrieval accuracy of large image databases has been improved as a result of reducing the semantic gap by combining the input sketch with relevance feedback. A further improvement of retrieval accuracy is expected by combining each stroke, and its order, of the input sketch with the relevance feedback. However, this leaves as a problem the fact that the effect of the relevance feedback substantially depends on the stroke order in the input sketch. Although it is theoretically possible to consider all the possible stroke orders, that would cause a realistic problem of creating an enormous amount of data. Consequently, the technique introduced in this paper intends to improve retrieval efficiency by effectively using the relevance feedback by means of conducting data mining of the sketch considering the similarity in the order of strokes. To ascertain the effectiveness of this technique, a retrieval experiment was conducted using 20,000 images of a collection, the Corel Photo Gallery, and the experiment was able to confirm an improvement in the retrieval efficiency.