In rich scattering environments, multiple antenna systems designed to accomplish spatial multiplexing have enormous potential of lifting the capacity of corresponding multiple input multiple output channels. In this paper, we present a new low complexity algorithm for decision feedback equalization detector in the SM scheme. The basic idea is to reduce the joint optimization problem to separate optimization problems to achieve better performance-complexity tradeoffs. Concretely, we separately optimize the detection order and the detector filters so that the complexity of the entire signal detection task is reduced. The new order search rule approximates the optimal Bell Labs layered space time (BLAST) approach from a geometrical perspective, and the detector filters are derived using a Cholesky based QR decomposition. The new algorithm is able to switch from zero forcing to minimum mean square error without additional operations and the computational effort is a small fraction of that in the optimal BLAST algorithm. Despite its low complexity, the error performance of new detector closely approximates that of the standard BLAST.

This paper reviews and discusses devices, circuits, and signal processing techniques for CMOS imaging SoC's based on column-parallel processing architecture. The pinned photodiode technology improves the noise characteristics at the device level to be comparable to CCD image sensors and as a result, low-noise design in CMOS image sensors has been shifted to the reduction of noise at the circuit level. Techniques for reducing the circuit noise are discussed. The performance of the imaging SoC's greatly depends on that of the analog-to-digital converter (ADC) used at the column. Three possible architectures of the column-parallel ADC are reviewed and their advantage and disadvantage are discussed. Finally, a few applications of the device and circuit techniques and the column-parallel processing architecture are described.

There are three well-known identification schemes: the Fiat-Shamir, GQ and Schnorr identification schemes. All of them are proven secure against the passive or active attacks under some number-theoretic assumptions. However, efficiencies of the reductions in those proofs of security are not tight, because they require "rewinding" a cheating prover. We show an identification scheme IDKEA1, which is an enhanced version of the Schnorr scheme. Although it needs the four exchanges of messages and slightly more exponentiations, the IDKEA1 is proved to be secure under the KEA1 and DLA assumptions with tight reduction. The idea underlying the IDKEA1 is to use an extractable commitment for prover's commitment. In the proof of security, the simulator can open the commitment in two different ways: one by the non-black-box extractor of the KEA1 assumption and the other through the simulated transcript. This means that we don't need to rewind a cheating prover and can prove the security without loss of the efficiency of reduction.

In this paper, we present an efficient variant of the Boneh-Franklin scheme that achieves a tight security reduction. Our scheme is basically an IBE scheme under two keys, one of which is randomly chosen and given to the user. It can be viewed as a continuation of an idea introduced by Katz and Wang; however, unlike the Katz-Wang variant, our scheme is quite efficient, as its ciphertext size is roughly comparable to that of the original full Boneh-Franklin scheme. The security of our scheme can be based on either the gap bilinear Diffie-Hellman (GBDH) or the decisional bilinear Diffie-Hellman (DBDH) assumptions.

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.

In this letter, a lattice-reduction-aided (LRA) minimum mean square error (MMSE) Tomlinson-Harashima precoding (THP) is proposed for multiple input multiple output (MIMO) systems. The extended channel is exploited to develop the LRA MMSE-THP based on the lattice reduction method. Simulation results show that the proposed scheme significantly outperforms the conventional MMSE THP and the LRA zero-forcing (ZF) THP and achieves full diversity order.

Recent theoretical and experimental studies indicate that spatial multiplexing (SM) systems have enormous potential for increasing the capacity of corresponding multiple input multiple output (MIMO) channels in rich scattering environments. In this paper, we propose a new recursion based algorithm for Bell Labs layered space time (BLAST) signal detection in SM systems. The new algorithm uses an inflated recursion in the initialization and a deflated recursion in the iteration stage: as a result, the complexity is greatly reduced and the irregularity issues are completely avoided. Compared with the conventional fastest recursive approach, the complexity of our proposal is lower by a factor of 2 and it is also very implementation friendly.

We propose a recursive clustering and order restriction (R-CORE) method for learning large-scale Bayesian networks. The proposed method considers a reduced search space for directed acyclic graph (DAG) structures in scoring-based Bayesian network learning. The candidate DAG structures are restricted by clustering variables and determining the intercluster directionality. The proposed method considers cycles on only cmax(«n) variables rather than on all n variables for DAG structures. The R-CORE method could be a useful tool in very large problems where only a very small amount of training data is available.

The present paper describes a quality enhancement of speech corrupted by additive background noise in a single channel system. The proposed approach is based on the introduction of perceptual criteria using a frequency-weighting filter in a subtractive-type enhancement process. This newly developed algorithm allows for an automatic adaptation in the time and frequency of the enhancement system and finds a suitable noise estimate according to the frequency of the corrupted speech. Experimental results show that the proposed approach can efficiently remove additive noise related to various types of noise corruption.

A nonlinear harmonic estimator (NHE) is proposed for extracting a harmonic signal and its fundamental frequency in the presence of white noise. This estimator is derived by applying an extended complex Kalman filter (ECKF) to a multiple sinusoidal model with state-representation and then efficiently specializing it for the case of harmonic estimation. The effectiveness of the NHE is verified using computer simulations.

This paper proposes a novel signal estimation method that uses a tensor product expansion. When a bivariable function, which is expressed by two-dimensional matrix, is subjected to conventional tensor product expansion, two single variable functions are calculated by minimizing the mean square error between the input vector and its outer product. A tensor product expansion is useful for feature extraction and signal compression, however, it is difficult to separate global noise from other signals. This paper shows that global noise, which is observed in almost all input signals, can be estimated by using a tensor product expansion where absolute error is used as the error function.

This paper proposes a new identifier scheme for Internet Indirection Infrastructure (i3). i3 is an overlay network on top of IP, and realizes rendezvous-based communications. It provides a general solution to deal with communication primitives such as host mobility, multicast and anycast. Although i3 provides flexible communication mechanisms, it is not optimized for mobile and wireless communications. Thus, three key problems still remain to be addressed: header overhead, multiple trigger updates and detection of a close i3 server after handover. The proposed identifier scheme, called local ID, significantly reduces the overhead without sacrificing the flexibility of i3. In a typical case, the local ID makes the total header size nearly half that of the original protocol. This paper also discusses how to adapt the local ID to various types of i3 primitives, so that a mobile host can receive all the benefits of i3 communications.

We present theoretical foundations about error estimations of the global Krylov subspace techniques for multiple-inputs multiple-outputs (MIMO) Interconnect reductions. Analytical relationships between Lyapunov functions of the original interconnect network and those of the reduced system generated by the global Arnoldi algorithm will be developed. Under this framework, a new moment matching reduced network is proposed. Also, we will show that the reduced system can be expressed as the original network with some additive perturbations.

Two versions of Krylov subspace order reduction techniques for VLSI interconnect reductions, including structure preserving reductions approach and adjoint networks approach, will be comparatively investigated. Also, we will propose a modified structure preserving reduction algorithm to speed up the projection construction in a linear order. The numerical experiment shows the high accuracy and low computational consumption of the modified method. In addition, it will be shown that the projection subspace generated from the structure-preserving approach and those from the adjoint networks approach are equivalent. Therefore, transfer functions of both reduced networks are identical.

A tri-template-based codes (TTBC) method is proposed to reduce test cost of intellectual property (IP) cores. In order to reduce test data volume (TDV), the approach utilizes three templates, i.e., all 0, all 1, and the previously applied test data, for generating the subsequent test data by flipping the inconsistent bits. The approach employs a small number of test channels I to supply a large number of internal scan chains 2I-3 such that it can achieve significant reduction in test application time (TAT). Furthermore, as a non-intrusive and automatic test pattern generation (ATPG) independent solution, the approach is suitable for IP core testing because it requires neither redesign of the core under test (CUT) nor running any additional ATPG for the encoding procedure. In addition, the decoder has low hardware overhead, and its design is independent of the CUT and the given test set. Theoretical analysis and experimental results for ISCAS 89 benchmark circuits have proven the efficiency of the proposed approach.

This paper studies the reduction among cyptographic functions. Our main result is that the prime factoring function IF does not reduce to the certified discrete logarithm function modulo a prime nor its variant with respect to some special reducibility, i.e. the range injection reducibility, under the assumption that the Heath-Brown conjecture is true and IFPF. Since there is no known direct relationship between these functions, this is the first result that could separate these functions. Our approach is based on the notion of the preimage functions.

This letter develops an efficient CPM demodulator which provides soft outputs for use in coded CPM. The proposed algorithm offers reduced-complexity soft output detection in which the number of matched filters and trellis states is appreciably reduced. The complexity reduction is achieved by approximating the CPM signal using the Laurent representation. A simulation study of iterative decoding of serially concatenated CPM with an outer code was performed. The performance degradation of the proposed algorithm relative to optimal full complexity generation of soft outputs was found to be small.

It is well-known that one of the best wavelet-based image compression techniques, called Wavelet Difference Reduction-WDR, has both simple algorithm and comparative rate-distortion results comparing to other coders in the literature. In this paper, we propose an algorithm to enhance the performance of WDR coder in a very efficient way. The methodology is highly based on the context adaptive model. High-order statistical context modeling is used for significant coefficients prediction by scanning order adaptation of WDR. In binary mode, the coder is clearly better than Set Partitioning in Hierarchical Trees (SPIHT). A new conditional Arithmetic Coding (AC) using array of contexts is specifically designed for WDR-based coder. Based on our simulation results of all images in the test set which covers various types of images, it is apparent that our proposed coder in AC mode generates the rate-distortion results that are superior to those of all other WDR-based coders in the literature. Furthermore, it is very competitive to SPIHT-AC and JPEG2000, the best coders, at all bit rates.

In situ observation of the adsorption process and reduction behavior of hemoglobin adsorbed on a bare glass surface was studied using slab optical waveguide (SOWG) spectroscopy. The peak position of the absorption band of hemoglobin adsorbed on the glass surface was almost the same as that of hemoglobin in solution. This result agrees with results previously reported by our group. The adsorbed hemoglobin molecules were also reduced by sodium dithionite solution. The adsorbed hemoglobin molecules still maintained their function in this experimental condition.

A novel UWB system for a new indoor short distance radio-communication is examined. Various types of UWB systems have been proposed in the literature. Particularly direct sequence (DS) systems and time hopping (TH) systems are attractive due to low power consumption and a simple transceiver construction. In this paper, we consider to apply modulated and modified Hermite pulses (MMHP) for both DS-UWB and TH-UWB systems. Furthermore, MMHP are extended to a novel pulse set referred as limited bandwidth MMHP set in order to reduce various interferences. It is composed of pseudo-orthogonal pulses that have both good auto-correlation characteristics in all orders and low cross-correlation characteristics between different orders. The proposed pulse set also have some specific notches, which can be used to reduce narrow-band interference (NBI). Additionally, we propose a novel pulse shape hopping that employs the proposed MMHP set. Multi-user interference (MUI) and inter-symbol interference (ISI) can be reduced by such a pulse shape hopping scheme for the DS or TH UWB signal format. Simulation results show significant performance improvements by using the proposed UWB system.