In this paper, we propose a high-throughput binary arithmetic coding architecture for CABAC (Context Adaptive Binary Arithmetic Coding) which is one of the entropy coding tools used in the H.264/AVC main and high profiles. The full CABAC encoding functions, including binarization, context model selection, arithmetic encoding and bits generation, are implemented in this proposal. The binarization and context model selection are implemented in a proposed binarizer, in which a FIFO is used to pack the binarization results and output 4 bins in one clock. The arithmetic encoding and bits generation are implemented in a four-stage pipeline with the encoding ability of 4 bins/clock. In order to improve the processing speed, the context variables access and update for 4 bins are paralleled and the pipeline path is balanced. Also, because of the outstanding bits issue, a bits packing and generation strategy for 4 bins paralleled processing is proposed. After implemented in verilog-HDL and synthesized with Synopsys Design Compiler using 90 nm libraries, this proposal can work at the clock frequency of 250 MHz and takes up about 58 K standard cells, 3.2 Kbits register files and 27.6 K bits ROM. The throughput of processing 1000 M bins per second can be achieved in this proposal for the HDTV applications.

The performance of the least-mean-square (LMS) beamformer is heavily dependent on the choice of the step-size, for it governs the convergence rate and steady-state excess mean squared error. To meet the conflicting requirement of low misadjustment, especially for the beamformer being modified in response to the multipath environmental changes, it needs to be controlled in a proper way. In this letter, we present an efficient adaptive step-size subarray LMS to achieve good performance. Simulation results are provided for illustrating the effectiveness of the proposed scheme.

Stream Control Transmission Protocol (SCTP) is a new transport layer protocol for the next generation Internet. SCTP is a connection-oriented protocol that carries over TCP's features but also supports UDP-like message-oriented data transmission. In this paper, we make use of SCTP's multi-streaming feature to transmit MPEG-4 video efficiently, and evaluate its transmission performance under the policy with/without differentiated retransmission. Moreover, to enhance the communication quality, we extend SCTP multi-streaming to realize selective retransmission policy. Our extension utilizes packet-by-packet timestamps to control retransmission of lost packets. By computer simulation, we show that SCTP can (1) improve the video quality by exploiting the multi-streaming and partial reliability features, (2) enhance the video transmission quality by adjusting SCTP fast retransmit threshold, and (3) SCTP with our selective retransmission extension can further improve the whole performance.

In a closed-loop scenario, the performance of transmit-diversity schemes for a multiple antenna system depends on the reliability of the channel state information (CSI). However, estimating the reliability of the instantaneous CSI at the transmitter is a challenging task. In this paper, we propose a robust transmit-diversity scheme for the case when the instantaneous CSI available at the transmitter is imperfect and its reliability is unknown to the transmitter. We show by simulation that our proposed scheme is efficient when the CSI reliability varies arbitrarily in every channel realization.

In this paper, we propose an exact analytical technique to evaluate the average capacity of a dual-hop OFDM relay system with decode-and-forward protocol in an independent and identical distribution (i.i.d.) Rayleigh fading channel. Four schemes, (no) matching "and" or "or" (no) power allocation, will be considered. First, the probability density function (pdf) for the end-to-end power channel gain for each scheme is described. Then, based on these pdf functions, we will give the expressions of the average capacity. Monte Carlo simulation results will be shown to confirm the analytical results for both the pdf functions and average capacities.

This paper proposes a self-taught classifier of gateways for hybrid SLAM. Gateways are detected and recognized by the self-taught classifier, which is a SVM classifier and self-taught in that its training samples are produced and labeled without user's intervention. Since the detection of gateways at the topological boundaries of an acquired metric map reduces computational complexity in partitioning the metric map into sub-maps as compared with previous hybrid SLAM approaches using spectral clustering methods, from O(2n) to O(n), where n is the number of sub-maps. This makes possible real time hybrid SLAM even for large-scale metric maps. We have confirmed that the self-taught classifier provides satisfactory consistency and computationally efficiency in hybrid SLAM through different experiments.

This paper proposes cooperative coding using cyclic delay diversity (CDD) for OFDM systems. The cooperative diversity is combined with channel coding while CDD is applied to the cooperative transmission of the multiple relays to improve the beneficial effects of the cooperating relays. Analyses of frame error probability (FEP) and the average channel power of the proposed scheme are shown. Simulation results show the frame error rate (FER) of the proposed scheme. The proposed scheme provides not only a simple code design and low system complexity compared to conventional space-time processing, but better FER and diversity gain compared to direct transmission and conventional cooperative coding without CDD.

We present the PCA self-cross bilateral filter for denoising multi-modal images. We firstly apply the principal component analysis for input multi-modal images. We next smooth the first principal component with a preliminary filter and use it as a supplementary image for cross bilateral filtering of input images. Among some preliminary filters, the undecimated wavelet transform is useful for effective denoising of various multi-modal images such as color, multi-lighting and medical images.

The aim of this research is to study the power energy cost reduction of the mobile telecom industry through the supervisor control and data acquisition (SCADA) system application during globalization and liberalization competition. Yet this management system can be proposed functions: operating monitors, the analysis on load characteristics and dropping the cost of management.

This paper proposes methods for accelerating DPA by using the CPU and the GPU in a parallel manner. The overhead of naive DPA evaluation software increases excessively as the number of points in a trace or the number of traces is enlarged due to the rapid increase of file I/O overhead. This paper presents some techniques, with respect to DPA-arithmetic and file handling, which can make the overhead of DPA software become not extreme but gradual as the increase of the amount of trace data to be processed. Through generic experiments, we show that the software, equipped with the proposed methods, using both CPU and GPU can shorten the time for evaluating the DPA resistance of devices by almost half.

In this letter, we propose a new tuning method of ε value, which is a parameter in the ε-filter, using a metric between signal distributions, i.e., Hellinger distance. The difference between the input and output signals is evaluated using Hellinger distance and used for the parameter tuning in the proposed method.

We have developed a one-to-many eigenvoice conversion (EVC) system that allows us to convert a single source speaker's voice into an arbitrary target speaker's voice using an eigenvoice Gaussian mixture model (EV-GMM). This system is capable of effectively building a conversion model for an arbitrary target speaker by adapting the EV-GMM using only a small amount of speech data uttered by the target speaker in a text-independent manner. However, the conversion performance is still insufficient for the following reasons: 1) the excitation signal is not precisely modeled; 2) the oversmoothing of the converted spectrum causes muffled sounds in converted speech; and 3) the conversion model is affected by redundant acoustic variations among a lot of pre-stored target speakers used for building the EV-GMM. In order to address these problems, we apply the following promising techniques to one-to-many EVC: 1) mixed excitation; 2) a conversion algorithm considering global variance; and 3) adaptive training of the EV-GMM. The experimental results demonstrate that the conversion performance of one-to-many EVC is significantly improved by integrating all of these techniques into the one-to-many EVC system.

We have developed a macro model, which allows us to describe precise LDMOS DC/AC characteristics. Characterization of anomalous gate input capacitance is the key issue in the LDMOS model development. We have newly employed a T-type distributed RC scheme for gate overlapped LDMOS drift region. The bias dependent resistance and capacitance are modeled independently in Verilog-A as R-model and PMOS-capacitance. The dividing factor of the distributed R is introduced to reflect the shield effect of the gate overlap capacitance. Comparison between the new model and measurement results has proven that the developed macro model reproduces accurately not only the gate input capacitance, but also DC characteristics.

This paper focuses on the problem of performance degradation in mismatched speech recognition. The F-Ratio analysis method is utilized to analyze the significance of different frequency bands for speech unit classification, and we find that frequencies around 1 kHz and 3 kHz, which are the upper bounds of the first and the second formants for most of the vowels, should be emphasized in comparison to the Mel-frequency cepstral coefficients (MFCC). The analysis result is further observed to be stable in several typical mismatched situations. Similar to the Mel-Frequency scale, another frequency scale called the F-Ratio-scale is thus proposed to optimize the filter bank design for the MFCC features, and make each subband contains equal significance for speech unit classification. Under comparable conditions, with the modified features we get a relative 43.20% decrease compared with the MFCC in sentence error rate for the emotion affected speech recognition, 35.54%, 23.03% for the noisy speech recognition at 15 dB and 0 dB SNR (signal to noise ratio) respectively, and 64.50% for the three years' 863 test data. The application of the F-Ratio analysis on the clean training set of the Aurora2 database demonstrates its robustness over languages, texts and sampling rates.

We propose a segment-based voice conversion technique using hidden Markov model (HMM)-based speech synthesis with nonparallel training data. In the proposed technique, the phoneme information with durations and a quantized F0 contour are extracted from the input speech of a source speaker, and are transmitted to a synthesis part. In the synthesis part, the quantized F0 symbols are used as prosodic context. A phonetically and prosodically context-dependent label sequence is generated from the transmitted phoneme and the F0 symbols. Then, converted speech is generated from the label sequence with durations using the target speaker's pre-trained context-dependent HMMs. In the model training, the models of the source and target speakers can be trained separately, hence there is no need to prepare parallel speech data of the source and target speakers. Objective and subjective experimental results show that the segment-based voice conversion with phonetic and prosodic contexts works effectively even if the parallel speech data is not available.

This paper presents a low-power System on Chip (SOC) architecture for the v2.0+EDR (Enhanced Data Rate) Bluetooth and its applications. Our design includes a link controller, modem, RF transceiver, Sub-Band Codec (SBC), Expanded Instruction Set Computer (ESIC) processor, and peripherals. To decrease power consumption of the proposed SOC, we reduce data transfer using a dual-port memory, including a power management unit, and a clock gated approach. We also address some of issues and benefits of reusable and unified environment on a centralized data structure and SOC verification platform. This includes flexibility in meeting the final requirements using technology-independent tools wherever possible in various processes and for projects. The other aims of this work are to minimize design efforts by avoiding the same work done twice by different people and to reuse the similar environment and platform for different projects. This chip occupies a die size of 30 mm2 in 0.18 µm CMOS, and the worst-case current of the total chip is 54 mA.

In this paper, we present the sexual dimorphism analysis in 3D human face and perform gender classification based on the result of sexual dimorphism analysis. Four types of features are extracted from a 3D human-face image. By using statistical methods, the existence of sexual dimorphism is demonstrated in 3D human face based on these features. The contributions of each feature to sexual dimorphism are quantified according to a novel criterion. The best gender classification rate is 94% by using SVMs and Matcher Weighting fusion method. This research adds to the knowledge of 3D faces in sexual dimorphism and affords a foundation that could be used to distinguish between male and female in 3D faces.

A novel Position-Invariant Robust Feature, designated as PIRF, is presented to address the problem of highly dynamic scene recognition. The PIRF is obtained by identifying existing local features (i.e. SIFT) that have a wide baseline visibility within a place (one place contains more than one sequential images). These wide-baseline visible features are then represented as a single PIRF, which is computed as an average of all descriptors associated with the PIRF. Particularly, PIRFs are robust against highly dynamical changes in scene: a single PIRF can be matched correctly against many features from many dynamical images. This paper also describes an approach to using these features for scene recognition. Recognition proceeds by matching an individual PIRF to a set of features from test images, with subsequent majority voting to identify a place with the highest matched PIRF. The PIRF system is trained and tested on 2000+ outdoor omnidirectional images and on COLD datasets. Despite its simplicity, PIRF offers a markedly better rate of recognition for dynamic outdoor scenes (ca. 90%) than the use of other features. Additionally, a robot navigation system based on PIRF (PIRF-Nav) can outperform other incremental topological mapping methods in terms of time (70% less) and memory. The number of PIRFs can be reduced further to reduce the time while retaining high accuracy, which makes it suitable for long-term recognition and localization.

Single event transient (SET) effects on original static cascade voltage switch logic (CVSL) exclusive-OR (EX-OR) circuits have been investigated using SPICE. SET simulation results have confirmed that the static CVSL EX-OR circuits have increased tolerance to SET. The static CVSL EX-OR circuit is more than 200 times harder than the conventional CMOS circuit.

A linear model for feedforward ring oscillators (FROs) is developed and oscillator characteristics are analyzed using the model. The model allows prediction of multiple oscillation modes as well as the oscillation frequency of each mode. The prediction agrees well with SPICE simulation results.