In this letter, we propose joint frequency offset and SNR estimation technique. The frequency offset may degrade the system performance greatly by deleterious effect. The proposed frequency offset estimation technique estimates frequency offset by employing the interpolation technique in the frequency domain. Also we propose SNR estimation technique using the estimated frequency offset for FFT-based system. The SNR estimated by the receiver can be used to adapt the demodulation algorithm to enhance its performance, as well as to provide the channel quality information. Simulation results show the performance of frequency offset and SNR estimator.

Orthogonal multicode direct sequence code division multiple access (DS-CDMA) has the flexibility in offering various data rate services. However, in a frequency-selective fading channel, the bit error rate (BER) performance is severely degraded since the othogonality among spreading codes is partially lost. In this paper, we apply frequency-domain equalization and antenna diversity combining, used in multi-carrier CDMA (MC-CDMA), to orthogonal multicode DS-CDMA in order to restore the code othogonality while achieving frequency and antenna diversity effect. It is found by computer simulations that the joint use of frequency-domain equalization and antenna diversity combining can significantly improve the BER performance of orthogonal multicode DS-CDMA in a frequency-selective fading channel.

In this report we present all-optical switches and modulators based on the intersubband transition in semiconductor quantum wells. The use of InGaAs/AlAsSb coupled double quantum well structures is proposed to facilitate intersubband transitions in the optical-communication band, and to reduce the intersubband absorption recovery time from several picoseconds to a few hundred femtoseconds by utilizing enhanced electron-phonon scattering. Subpicosecond all-optical gating and modulation in coupled double quantum wells are observed using pump-probe experiments at optical-communication wavelengths. The results indicate that the intersubband transition in this structure is very useful for ultrafast all-optical switching devices.

In this paper, based on maximum neural network, we propose a new parallel algorithm that can escape from local minima and has powerful ability of searching the globally optimal or near-optimum solution for the maximum clique problem (MCP). In graph theory a clique is a completely connected subgraph and the MCP is to find a clique of maximum size of a graph. The MCP is a classic optimization problem in computer science and in graph theory with many real-world applications, and is also known to be NP-complete. Lee and Takefuji have presented a very powerful neural approach called maximum neural network for this NP-complete problem. The maximum neural model always guarantees a valid solution and greatly reduces the search space without a burden on the parameter-tuning. However, the model has a tendency to converge to the local minimum easily because it is based on the steepest descent method. By adding a negative self-feedback to the maximum neural network, we proposed a parallel algorithm that introduces richer and more flexible chaotic dynamics and can prevent the network from getting stuck at local minima. After the chaotic dynamics vanishes, the proposed algorithm is then fundamentally reined by the gradient descent dynamics and usually converges to a stable equilibrium point. The proposed algorithm has the advantages of both the maximum neural network and the chaotic neurodynamics. A large number of instances have been simulated to verify the proposed algorithm.

Iris recognition is used to identify a user based on the iris texture information which exists between the white sclera and the black pupil. For fast iris recognition, it is very important to capture user's focused eye image at fast speed. If not, the total recognition time is increased and it makes the user feel much inconvenience. In previous researches and systems, they use the focusing method which has been used for general landscape scene without considering the characteristics of iris image. So, they take much focusing time sometimes, especially in case of the user with glasses. To overcome such problems, we propose a new iris image acquisition method to capture user's focused eye image at very fast speed based on the corneal specular reflection. Experimental results show that the focusing time for both the users with glasses and without glasses is average 480 ms and we can conclude our method can be used for the real-time iris recognition camera.

In this paper we apply a parallel adaptive solution algorithm to simulate nanoscale double-gate metal-oxide-semiconductor field effect transistors (MOSFETs) on a personal computer (PC)-based Linux cluster with the message passing interface (MPI) libraries. Based on a posteriori error estimation, the triangular mesh generation, the adaptive finite volume method, the monotone iterative method, and the parallel domain decomposition algorithm, a set of two-dimensional quantum correction hydrodynamic (HD) equations is solved numerically on our constructed cluster system. This parallel adaptive simulation methodology with 1-irregular mesh was successfully developed and applied to deep-submicron semiconductor device simulation in our recent work. A 10 nm n-type double-gate MOSFET is simulated with the developed parallel adaptive simulator. In terms of physical quantities and refined adaptive mesh, simulation results demonstrate very good accuracy and computational efficiency. Benchmark results, such as load-balancing, speedup, and parallel efficiency are achieved and exhibit excellent parallel performance. On a 16 nodes PC-based Linux cluster, the maximum difference among CPUs is less than 6%. A 12.8 times speedup and 80% parallel efficiency are simultaneously attained with respect to different simulation cases.

In this paper we propose a parallel composition based adaptive notch filter for eliminating sinusoidal signals whose frequencies are unknown. The proposed filter which is implemented using second order all-pass filter and a band-pass filter can achieve high convergence speed by using the output of an additional band-pass filter to update the coefficients of the notch filter. The high convergence speed of the proposed notch filter is obtained by reducing an effect that an updating term of coefficient for adaptation of a notch filter significantly increases when the notch frequency approaches the sinusoidal frequency. In this paper, we analyze such effect obtained by the additional band-pass filter. We also present an analysis of a convergence performance of cascaded system of the proposed notch filter for eliminating multiple sinusoids. Simulation results have shown the effectiveness of the proposed adaptive notch filter.

This paper proposes an efficient query evaluation scheme for a mediator system intended to integrate heterogeneous computing environment in terms of operating systems, database management systems, and other software. Most of mediator systems transform a global query into a set of sub-queries based on their target remote servers. Each sub-query is evaluated by the query modification method to evaluate a global query. However, it is possible to reduce the evaluation cost of a global query when the results of frequently requested sub-queries are materialized in a mediator. In a mediator, its integrating schema can be incrementally modified and the evaluation frequency of a global query can also be continuously varied. In order to select the optimized set of materialized sub-queries with respect to their current evaluation frequencies, the proposed method applies a decay factor for modeling the recent access behavior of each sub-query. In other words, the latest access of a sub-query gets the highest attention in the selection process of materialized sub-queries. As a result, it is possible to adjust the optimized set of materialized sub-queries adaptively according to the recent changes in the evaluation frequencies of sub-queries. Since finding the optimum solution of this problem is NP-hard, it takes too long to be used in practice when the number of sub-queries is large. Consequently, given the size of mediator storage, the rank-based selection algorithm proposed in this paper finds the set of materialized sub-queries which minimizes the total evaluation cost of global queries in linear search complexity.

Scientific computations for diffusion equations and ANNs (Artificial Neural Networks) are data intensive tasks accompanied by heavy memory access; on the other hand, their computational complexities are relatively low. Thus, this type of tasks naturally maps onto SIMD (Single Instruction Multiple Data stream) parallel processing with distributed memory. This paper proposes a high performance acceleration processor of which architecture is optimized for scientific computing using diffusion equations and ANNs. The proposed architecture includes a customized instruction set and specific hardware resources which consist of a control unit (CU), 16 processing units (PUs), and a non-linear function unit (NFU) on chip. They are effectively connected with dedicated ring and global bus structure. Each PU is equipped with an address modifier (AM) and 16-bit 1.5 k-word local memory (LM). The proposed processor can be easily expanded by multi-chip expansion mode to accommodate to a large scale parallel computation. The prototype chip is implemented with FPGA. The total gate count is about 1 million with 530, 432-bit embedded memory cells and it operates at 15 MHz. The functionality and performance of the proposed processor is verified with simulation of oil reservoir problem using diffusion equations and character recognition application using ANNs. The execution times of two applications are compared with software realizations on 1.7 GHz Pentium IV personal computer. Though the proposed processor architecture and the instruction set are optimized for diffusion equations and ANNs, it provides flexibility to program for many other scientific computation algorithms.

The alignment of biological sequences is a crucial tool in molecular biology and genome analysis. A wide variety of approaches has been proposed for multiple sequence alignment problem; however, some of them need prerequisites to help find the best alignment or some of them may suffer from the drawbacks of complexity and memory requirement so they can be only applied to cases with a limited number of sequences. In this paper, we view the multiple sequence alignment problem as an optimization problem and propose a heuristic-based genetic algorithm (GA) approach to solve it. The heuristic/GA hybrid yields better results than other well-known packages do. Experimental results are presented to illustrate the feasibility of the proposed approach.

In this paper, Message Passing Interface (MPI) techniques are used to implement high-order full 3-D Navier-Stokes equations in multi-domain applications. A two-domain interface with five-point overlapping used previously is expanded to a multi-domain computation. There are normally two approaches for this expansion. One is to break up the domain into two parts through domain decomposition (say, one overlapping), then using MPI directives to further break up each domain into n parts. Another is to break the domain up into 2n parts with (2n-1) overlappings. In our present effort, the latter approach is used and finite-size overlappings are employed to exchange data between adjacent multi-dimensional sub-domains. It is an alternative way to parallelize the high-order full 3-D Navier-Stokes equations into multi-domain applications without adding much complexity. Results with high-order boundary treatments show consistency among multi-domain calculations and single-domain results.

We describe the characteristics of all-optical switching schemes based on semiconductor optical amplifiers (SOAs), with particular emphasis on the role of the fast carrier dynamics. The SOA response to a single short pulse as well as to a data-modulated pulse train is investigated and the properties of schemes relying on cross-gain as well as cross-phase modulation are discussed. The possible benefits of using SOAs with quantum dot active regions are theoretically analyzed. The bandfilling characteristics and the presence of fast capture processes may allow to reach bitrates in excess of 100 Gb/s even for simple cross-gain modulation schemes.

Reduced-state sequence estimation (RSSE) for trellis-coded modulation (TCM) in cyclic prefixed single carrier (CPSC) with minimum mean-square error-linear equalization (MMSE-LE) on frequency-selective Rayleigh fading channels is proposed. The Viterbi algorithm (VA) is used to search for the best path through the reduced-state trellis combined equalization and TCM decoding. Computer simulations confirm the symbol error probability of the proposed scheme.

This letter considers multiple access systems without bandwidth expansion. To improve the spectral efficiency, each user employs a QPSK modulation. The orientation of QPSK constellations is designed to maximize the minimum distance of the superimposed symbol constellation. The upper and lower bounds for the error performance of the proposed design demonstrate its advantage.

In this paper, we propose a statistical method of time synchronization for computer clocks that have precisely frequency-synchronized oscillators. This method not only improves the accuracy of time synchronization but also prevents degradation in the frequency stability of the precise oscillators when the errors in the measured time offsets between computer clocks caused by network traffic possess a Gaussian distribution. Improved accuracy of time synchronization is achieved by estimating the confidence interval of the measured time offsets between the clocks. Degradation in frequency stability is prevented by eliminating unnecessary time correction for the computer clock, because time correction generally causes changes in the frequency accuracy and stability of the precise oscillators. To eliminate unnecessary time correction, our method uses an extended hypothesis test of the difference between the current mean and the mean at the last time adjustment to determine whether time correction is needed. Evaluation by simulating changes in the time offset of the existing ISDN clock synchronization system showed that this method achieves accurate time and stable frequency synchronization.

The joint use of frequency-domain equalization and antenna diversity is presented for single-carrier (SC) transmission in a frequency-selective fading channel. Frequency-domain equalization techniques using minimum mean square error (MMSE), orthogonal restoration combining (ORC) and maximum ratio combining (MRC), those used in multi-carrier code division multiple access (MC-CDMA), are considered. As antenna diversity techniques, receive diversity and delay transmit diversity (DTD) are considered. Bit error rate (BER) performance achievable with the joint use of frequency-domain equalization and antenna diversity is evaluated by computer simulation.

Differentiated Services architecture provides a framework that enables relative differentiation of Assured Forwarding (AF) service. The differentiation is quantified by QoS parameters in terms of loss probability and maximum delay. We develop herein an efficient model to compute resource allocation in terms of buffer and service rate that satisfies the QoS differentiation between classes of service. To evaluate the performance of the proposed model, we conducted extensive simulation on both single-node and multi-node cases. The simulation studies show that the model can provide an efficient method to allocate network resources for aggregated traffic.

There have been many researches on indexing and querying XML data. One of the important themes is how to efficiently process XML query represented by path expression. The most straightforward approach to process these queries is to traverse the hierarchy of XML document by top-down or bottom-up manner. However it may be fairly inefficient because the overhead of traversing the XML data can be high. In addition, most of the proposed indexing and retrieval schemes assume static environment where there are no updates on the parts of XML data. In this paper we propose a novel indexing and query processing scheme that can process both XML query represented by path expression efficiently and dynamic updates on XML data promptly. Experimental results show that our proposed scheme achieves better performance than that of the previous ones.

Many diverse methods have been developed in the field of biometric identification as a greater emphasis is placed on human-friendliness in the area of intelligent systems. One emerging method is the use of human footprint. However, in the previous research, there were some limitations resulting from the spatial resolution of sensors. One possible method to overcome this limitation is through the use additional information such as dynamic walking information in dynamic footprint. In this study, we suggest a new person recognition scheme based on overlapped foot shape and COP (Center Of Pressure) trajectory during one-step walking. And, we show the usefulness of the suggested method, obtaining a 98.6% recognition rate in our experiment with eleven people.

This paper describes a new speech enhancement system that employs a microphone array with post-processing based on minimum mean-square error short-time spectral amplitude (MMSE-STSA) estimator. To get more accurate MMSE-STSA estimator in a microphone array, modification and refinement procedure are carried out from each microphone output. Performance of the proposed system is compared with that of other methods using a microphone array. Noise removal experiments for white and pink noises demonstrate the superiority of the proposed speech enhancement system to others with a microphone array in average output SNRs and cepstral distance measures.