This paper presents discussion about channel fluctuation on channel estimation in digital terrestrial television broadcasting. This channel estimation uses a two-dimensional (2D) filter. In our previous work, only a structure of a lattice is considered for generation of nonrectangular 2D filter. We investigate generation of nonrectangular 2D filter with adaptive method, because we should refer to not only a lattice but also channel conditions. From the computer simulations, we show that bit error rate of the proposed filter is improved compared to that of the filter depending on only lattices.

A tree-shellable function is a positive Boolean function which can be represented by a binary decision tree whose number of paths from the root to a leaf labeled 1 equals the number of prime implicants. In this paper, we consider the tree-shellability of DNFs with restrictions. We show that, for read-k DNFs, the number of terms in a tree-shellable function is at most k2. We also show that, for k-DNFs, recognition of ordered tree-shellable functions is NP-complete for k=4 and tree-shellable functions can be recognized in polynomial time for constant k.

We developed test data compression scheme for scan-based BIST, aiming to compress test stimuli and responses by more than 100 times. As scan-BIST architecture, we adopt BIST-Aided Scan Test (BAST), and combines four techniques: the invert-and-shift operation, run-length compression, scan address partitioning, and LFSR pre-shifting. Our scheme achieved a 100x compression rate in environments where Xs do not occur without reducing the fault coverage of the original ATPG vectors. Furthermore, we enhanced the masking logic to reduce data for X-masking so that test data is still compressed to 1/100 in a practical environment where Xs occur. We applied our scheme to five real VLSI chips, and the technique compressed the test data by 100x for scan-based BIST.

To achieve high recognition performance for a wide variety of noise and for a wide range of signal-to-noise ratio, this paper presents methods for integration of four noise reduction algorithms: spectral subtraction with smoothing of time direction, temporal domain SVD-based speech enhancement, GMM-based speech estimation and KLT-based comb-filtering. In this paper, we proposed two types of combination methods of noise suppression algorithms: selection of front-end processor and combination of results from multiple recognition processes. Recognition results on the CENSREC-1 task showed the effectiveness of our proposed methods.

New multimedia services over cellular/WLAN overlay networks require different Quality of Service (QoS) levels. Therefore, an efficient network management system is necessary in order to realize QoS sensitive multimedia services while enhancing network performance. In this paper, we propose a new online network management framework for overlay networks. Our online approach to network management exhibits dynamic adaptability, flexibility, and responsiveness to the traffic conditions in multimedia networks. Simulation results indicate that our proposed framework can strike the appropriate balance between performance criteria under widely varying diverse traffic loads.

This paper proposes a robust omnidirectional audio-visual (AV) talker localizer for AV applications. The proposed localizer consists of two innovations. One of them is robust omnidirectional audio and visual features. The direction of arrival (DOA) estimation using an equilateral triangular microphone array, and human position estimation using an omnidirectional video camera extract the AV features. The other is a dynamic fusion of the AV features. The validity criterion, called the audio- or visual-localization counter, validates each audio- or visual-feature. The reliability criterion, called the speech arriving evaluator, acts as a dynamic weight to eliminate any prior statistical properties from its fusion procedure. The proposed localizer can compatibly achieve talker localization in a speech activity and user localization in a non-speech activity under the identical fusion rule. Talker localization experiments were conducted in an actual room to evaluate the effectiveness of the proposed localizer. The results confirmed that the talker localization performance of the proposed AV localizer using the validity and reliability criteria is superior to that of conventional localizers.

In this paper, we analyze the effects of IQ (In-phase/Quadrature-phase) imbalance at both transmitter and receiver of OFDM (Orthogonal Frequency Division Multiplexing) system and show that more diversity gain can be achieved even though there are unwanted IQ imbalance. When mixed sub-carriers within an OFDM symbol due to the IQ imbalance undergo frequency selective channels, additional diversity effects are expected during the demodulation process. Simulation results on the symbol error rate (SER) performance with ML (Maximum Likelihood) and OSIC (Ordered Successive Interference Cancellation) receiver show that significant performance gain can be achieved with the diversity gain caused by the IQ imbalance combined with the frequency selective channels.

We propose a noise suppression method based on multi-model compositions and multi-pass search. In real environments, input speech for speech recognition includes many kinds of noise signals. To obtain good recognized candidates, suppressing many kinds of noise signals at once and finding target speech is important. Before noise suppression, to find speech and noise label sequences, we introduce multi-pass search with acoustic models including many kinds of noise models and their compositions, their n-gram models, and their lexicon. Noise suppression is frame-synchronously performed using the multiple models selected by recognized label sequences with time alignments. We evaluated this method using the E-Nightingale task, which contains voice memoranda spoken by nurses during actual work at hospitals. The proposed method obtained higher performance than the conventional method.

We propose a noise suppression algorithm with the Kalman filter theory. The algorithm aims to achieve robust noise suppression for the additive white and colored disturbance from the canonical state space models with (i) a state equation composed of the speech signal and (ii) an observation equation composed of the speech signal and additive noise. The remarkable features of the proposed algorithm are (1) applied to adaptive white and colored noises where the additive colored noise uses babble noise, (2) realization of high performance noise suppression without sacrificing high quality of the speech signal despite simple noise suppression using only the Kalman filter algorithm, while many conventional methods based on the Kalman filter theory usually perform the noise suppression using the parameter estimation algorithm of AR (auto-regressive) system and the Kalman filter algorithm. We show the effectiveness of the proposed method, which utilizes the Kalman filter theory for the proposed canonical state space model with the colored driving source, using numerical results and subjective evaluation results.

In this comment we point out that the mapping from carry-propagation adders to carry-save adders in the context of shift-and-add multiplication is inconsistent. Based on this it is shown that the implementation in Ref.[1] does not achieve any complexity reduction in practice.

In this paper, proactive data filtering (PDF) algorithm is proposed for data aggregation (or data fusion) in wireless sensor networks. The objective of the algorithm is to further reduce the energy consumption when sensor nodes perform data aggregation. In many applications, the sensor field will be overwhelmed by unnecessary and redundant sensory information when the sink node disseminates a query throughout the sensor field. In order to reduce the energy consumption, our scheme employs intelligent decision logic in the sensor node which delays or deactivates the transmission of its response. A performance evaluation shows that data aggregation with the PDF significantly improves energy-efficiency.

This paper proposes a likelihood estimation method for reduced-complexity maximum-likelihood (ML) detectors in a multiple-input multiple-output (MIMO) spatial-multiplexing (SM) system. Reduced-complexity ML detectors, e.g., Sphere Decoder (SD) and QR decomposition (QRD)-M algorithm, are very promising as MIMO detectors because they can estimate the ML or a quasi-ML symbol with very low computational complexity. However, they may lose likelihood information about signal vectors having the opposite bit to the hard decision and bit error rate performance of the reduced-complexity ML detectors are inferior to that of the ML detector when soft-decision decoding is employed. This paper proposes a simple estimation method of the lost likelihood information suitable for the reduced-complexity ML detectors. The proposed likelihood estimation method is applicable to any reduced-complexity ML detectors and produces accurate soft-decision bits. Computer simulation confirms that the proposed method provides excellent decoding performance, keeping the advantage of low computational cost of the reduced-complexity ML detectors.

Test compression / decompression scheme for reducing the test application time and memory requirement of an LSI tester has been proposed. In the scheme, the employed coding algorithms are tailored to a given test data, so that the tailored coding algorithm can highly compress the test data. However, these methods have some drawbacks, e.g., the coding algorithm is ineffective in extra test data except for the given test data. In this paper, we introduce an embedded decompressor that is reconfigurable according to coding algorithms and given test data. Its reconfigurability can overcome the drawbacks of conventional decompressors with keeping high compression ratio. Moreover, we propose an architecture of reconfigurable decompressors for four variable-length codings. In the proposed architecture, the common functions for four codings are implemented as fixed (or non-reconfigurable) components so as to reduce the configuration data, which is stored on an ATE and sent to a CUT. Experimental results show that (1) the configuration data size becomes reasonably small by reducing the configuration part of the decompressor, (2) the reconfigurable decompressor is effective for SoC testing in respect of the test data size, and (3) it can achieve an optimal compression of test data by Huffman coding.

To precisely model the time dependency of features is one of the important issues for speech recognition. Segmental unit input HMM with a dimensionality reduction method has been widely used to address this issue. Linear discriminant analysis (LDA) and heteroscedastic extensions, e.g., heteroscedastic linear discriminant analysis (HLDA) or heteroscedastic discriminant analysis (HDA), are popular approaches to reduce dimensionality. However, it is difficult to find one particular criterion suitable for any kind of data set in carrying out dimensionality reduction while preserving discriminative information. In this paper, we propose a new framework which we call power linear discriminant analysis (PLDA). PLDA can be used to describe various criteria including LDA, HLDA, and HDA with one control parameter. In addition, we provide an efficient selection method using a control parameter without training HMMs nor testing recognition performance on a development data set. Experimental results show that the PLDA is more effective than conventional methods for various data sets.

The author developed a GaAs wideband IQ modulator IC, which is utilized in RF signal source instruments with direct-conversion architecture. The layout is fully symmetric to obtain a temperature-stable operation. However, the actual temperature drift of EVM (Error Vector Magnitude) is greater in some frequency and temperature ranges than the first generation IC of the same architecture. For applications requiring the precision of electric instrumentation, temperature drift is highly critical. This paper clarifies that linear phase error is the dominant factor causing the temperature drift. It also identifies that such temperature drift of linear phase error is due to equivalent series impedance, especially parasitic capacitance of the phase shifter. This effect is verified by comparing the SSB measurements to a mathematical simulation using an empirical temperature-dependent small-signal FET model.

A new linear prediction analysis method for multichannel signals was devised, with the goal of enhancing the compression performance of the MPEG-4 Audio Lossless Coding (ALS) compliant encoder and decoder. The multichannel coding tool for this standard carries out an adaptively weighted subtraction of the residual signals of the coding channel from those of the reference channel, both of which are produced by independent linear prediction. Our linear prediction method tries to directly minimize the amplitude of the predicted residual signal after subtraction of the signals of the coding channel, and the method has been implemented in the MPEG-4 ALS codec software. The results of a comprehensive evaluation show that this method reduces the size of a compressed file. The maximum improvement of the compression ratio is 14.6% which is achieved at the cost of a small increase in computational complexity at the encoder and without increase in decoding time. This is a practical method because the compressed bitstream remains compliant with the MPEG-4 ALS standard.

It is well known that cooperative transmission among the single antenna wireless nodes and a proper combining at destination can obtain spatial diversity. In this paper, we introduce a new form of combining technique in cooperative communication. For a coded transmission scheme code-combining can obtain a near optimal low rate code by combining repeated codewords. Instead of MRC (maximal ratio combining) based combining of received coded packets from source and relays, we propose a simple code-combining at destination. For same data rate and power consumption code-combining offers better or similar performance with less complexity than MRC. Moreover using a puncturing technique at the relay we can get a same diversity order as MRC with reduced packet relaying time; equivalently, with higher data rate for over all system. This reduction of transmission time at relay allows us to increase the diversity order by using more than one relay for one source; where each relay forwards a punctured portion of received data. Alternatively, when the relays are not available to improve diversity order, we can use only one relay to cooperate M source nodes where all sources obtain a diversity order of 2 with a higher data rate.

Error concealment at a decoder is an efficient method to reduce the degradation of visual quality caused by channel errors. In this paper, we propose a novel spatio-temporal error concealment algorithm based on the spatial-temporal fading (STF) scheme which has been recently introduced. Although STF achieves good performance for the error concealment, several drawbacks including blurring still remain in the concealed blocks. To alleviate these drawbacks, in the proposed method, hybrid approaches with adaptive weights are proposed. First, the boundary matching algorithm and the decoder motion vector estimation which are well-known temporal error concealment methods are adaptively combined to compensate for the defect of each other. Then, an edge preserved method is utilized to reduce the blurring effects caused by the bilinear interpolation for spatial error concealment. Finally, two concealed results obtained by the hybrid spatial and temporal error concealment are pixel-wisely blended with adaptive weights. Experimental results exhibit that the proposed method outperforms conventional methods including STF in terms of the PSNR performance as well as subjective visual quality, and the computational complexity of the proposed method is similar to that of STF.

In this paper, an energy-collection-based non-coherent IR-UWB receiver allowing low complexity and low power consumption is proposed for short range data communication. The proposed receiver consists of an on-the-fly integrator, a 1-bit digital sampler, a pre-processor and a digital symbol synchronizer. The on-the-fly integrator for energy collection and the 1-bit digital sampler reduce complexity of IR-UWB system. Furthermore, with a simple digital filter in the pre-processing unit, SNR and robustness of the receiver against time-varying channel are enhanced. Also the receiver complexity is diminished by a simple scheme of symbol synchronization based on rough time information about incoming pulses, not requiring exact timing information. The performance of the proposed receiver is simulated based on IEEE 802.15.4a channel model and the algorithms are implemented and verified on a FPGA.

In this review paper we showcase recent activities on silicon photonics science and technology research in Hong Kong regarding two important topical areas--microresonator devices and optical nonlinearities. Our work on silicon microresonator filters, switches and modulators have shown promise for the nascent development of on-chip optoelectronic signal processing systems, while our studies on optical nonlinearities have contributed to basic understanding of silicon-based optically-pumped light sources and helium-implanted detectors. Here, we review our various passive and electro-optic active microresonator devices including (i) cascaded microring resonator cross-connect filters, (ii) NRZ-to-PRZ data format converters using a microring resonator notch filter, (iii) GHz-speed carrier-injection-based microring resonator modulators and 0.5-GHz-speed carrier-injection-based microdisk resonator modulators, and (iv) electrically reconfigurable microring resonator add-drop filters and electro-optic logic switches using interferometric resonance control. On the nonlinear waveguide front, we review the main nonlinear optical effects in silicon, and show that even at fairly modest average powers two-photon absorption and the accompanied free-carrier linear absorption could lead to optical limiting and a dramatic reduction in the effective lengths of nonlinear devices.