The Japan Aerospace Exploration Agency (JAXA) plans to launch a geostationary satellite called Engineering Test Satellite VIII (ETS-VIII) in FY 2006. In this paper, a microstrip line array antenna, which has a very simple structure, is introduced to radiate a circularly polarized wave aiming at ETS-VIII applications. This antenna consists of a triangular conducting line with its vertexes rounded off, located above a ground plane, with a gap on one of its side to produce a circular polarization. The proposed antenna is analyzed by numerical simulations for a single element as well as for a three elements array configuration and the possibility of beam-switching in the azimuth space is experimentally confirmed in the latter case. It is found that by properly feeding the elements constituting the array antenna, for an elevation angle El = 48in Tokyo area, three beams are created in the conical-cut direction with a minimum gain more than 6.6 dBic and an axial ratio less than 3 dB.

In this letter, we propose a cdma2000 based MC-CDMA scheme which inherits the same architecture and bandwidth of forward link packet data channel of cdma2000 1x EV-DV. The system utilizes no cyclic prefix, and it uses the bandwidth efficient iterative technique [6] to recover cyclicity of OFDM symbol of the MC-CDMA system to achieve backward compatibility with 1x EV-DV system. We report that the link-level performance of our proposed system is significantly better than previous equalizer-based scheme [7] in frequency selective fading channels.

This paper proposes a robust fuzzy integral controller for output regulating a class of affine nonlinear systems subject to a bias reference to the origin. First, a common biased fuzzy model is introduced for a class of continuous/discrete-time affine nonlinear systems, such as dc-dc converters, robotic systems. Then, combining an integrator and parallel distributed compensators, the fuzzy integral regulator achieves an asymptotic regulation. Moreover, when considering disturbances or unstructured certainties, a virtual reference model is presented and provides a robust gain design via LMI techniques. In this case, H∞ performances is guaranteed. Note that the information regarding the operational point and bias terms are not required during the controller implementation. Thus, the controller can be applied to a multi-task regulation. Finally, three numerical simulations show the expected results.

For various applications in image, communications and signal processing, two-dimensional (2-D) generalized orthogonal (GO) sequences, that is, 2-D sequences with zero correlation zone (ZCZ) and 2-D complementary orthogonal (CO) sequences with ZCZ, are widely investigated. New lower bounds for 2-D GO sequences, based on matrix theory on rank, are derived and presented, some examples that attain these lower bounds are given. As a direct application to our results, upper bound on family size of 2-D mutually complementary orthogonal (MCO) codes defined by Luke [9] is proposed.

In this paper, we introduce a low computing post processing algorithm to simultaneously suppress blocking and ringing artifacts of compressed video sequences. A new regularization function to incorporate smoothness to neighboring pixels is defined, where the function is composed of four sub-functions combined with pixel-based data fidelity and smoothing terms. Therefore, the solution can be obtained without inverse matrix or vector-matrix computation, so that low complexity implementation is possible. In addition, the regularization parameter controlling the relative importance between the data fidelity and the degree of smoothness is estimated from the available overhead information in decoder, such as, macroblock type and quantization step size. The experimental results show the capability and efficiency of the proposed algorithm.

In this paper, we propose a hybrid fine-tuned multi-objective memetic algorithm hybridizing different solution fitness evaluation methods for global exploitation and exploration. To search across all regions in objective space, the algorithm uses a widely diversified set of weights at each generation, and employs a simulated annealing to optimize each utility function. For broader exploration, a grid-based technique is adopted to discover the missing nondominated regions on existing tradeoff surface, and a Pareto-based local perturbation is performed to reproduce incrementing solutions trying to fill up the discontinuous areas. Additional advanced feature is that the procedure is made dynamic and adaptive to the online optimization conditions based on a function of improvement ratio to obtain better stability and convergence of the algorithm. Effectiveness of our approach is shown by applying it to multi-objective 0/1 knapsack problem (MOKP).

A low-power FPGA design approach is proposed based on a fine-grain VDD control scheme called micro-VDD-hopping. Four configurable logic blocks (CLBs) are grouped into one block where VDD is shared. In the micro-VDD-hopping scheme, VDD in each block is changed between VDDH (high VDD) and VDDL (low VDD) spatially and temporally in order to achieve lower power without performance degraded. A low-power level shifter that has less contention is also proposed for low-swing inter-block signals. The FPGA incorporates the Zigzag power-gating scheme, in which special care has been taken to cope with a sneak leakage-path problem. A test chip was fabricated using a 0.35-µm CMOS technology, together with the conventional fixed-VDD FPGA for comparison. Measurement results show that dynamic power in the proposed scheme can be reduced by 86% when a frequency is half of the maximum one. Simulation using a 90-nm CMOS technology shows that leakage power can be reduced by 97%, when the proposed method is used. The area overhead of the proposed FPGA is 2%.

Stratospheric platforms have been recently proposed as a new wireless infrastructure for realizing the next generation of communication systems. To provide high quality services, an investigation of the wireless stratospheric platform channel is essential. This paper proposes a definition and describes an analysis of the wireless channel for the link between stratospheric platforms and terrestrial mobile users based on an experiment in a semi-urban environment. Narrowband channel characteristics are presented in terms of Ricean factor (K factor) and local mean received power over a wide range of elevation angles ranging from 10to 90. Finally, we evaluated average bit error probability based on the proposed channel model to examine the channel performance. For the environment in which the measurements were conducted, we find that elevation angles greater than 40yield better performance.

We propose a progressive transform-based phase unwrapping (PU) technique that employs a recursive structure. Each stage, which is identical with others in the construction, performs PU by FFT method that yields a solution and a residual phase error as well. The residual phase error is then reprocessed by the following stages. This scheme effectively improves the gradient estimate of the noisy wrapped phase image, which is unrecoverable by conventional global PU methods. Additionally, by incorporating computational strength of the transform PU method in a recursive system, we can realize a progressive PU system for prospective near real-time topographic-mapping radar and near real-time medical imaging system (such as MRI thermometry and MRI flow imager). PU performance of the proposed system and the conventional PU methods are evaluated by comparing their residual error quantitatively with a fringe-density-related error metric called FZX (fringe's zero-crossing) number. Experimental results for simulated and real InSAR phase images show significant, progressive improvement over conventional ones of a single-stage system, which demonstrates the high applicability of the proposed method.

In this letter, a novel pilot-aided inter-carrier interference (ICI) self-cancellation scheme is proposed for use in orthogonal frequency division multiplexing (OFDM) systems. The proposed scheme maps both modulated data symbols and pre-defined pilot symbols onto non-neighboring sub-carriers with weighting coefficients of +1 and -1. With the aid of pilot symbols, a more accurate estimation of frequency offsets can be obtained, and the ICI self-cancellation demodulation can be operated properly.

We propose a cell library development methodology for throughput enhancement of character projection equipment. First, an ILP (Integer Linear Programming)-based cell selection is proposed for the equipment for which both of the CP (Character Projection) and VSB (Variable Shaped Beam) methods are available, in order to minimize the number of electron beam (EB) shots, that is, time to fabricate chips. Secondly, the influence of cell directions on area and delay time of chips is examined. The examination helps to reduce the number of EB shots with a little deterioration of area and delay time because unnecessary directions of cells can be removed. Finally, a case study is shown in which the numbers of EB shots are shown for several cases.

A discriminative modeling is applied to optimize the structure of a Partly-Hidden Markov Model (PHMM). PHMM was proposed in our previous work to deal with the complicated temporal changes of acoustic features. It can represent observation dependent behaviors in both observations and state transitions. In the formulation of the previous PHMM, we used a common structure for all models. However, it is expected that the optimal structure which gives the best performance differs from category to category. In this paper, we designed a new structure optimization method in which the dependence of the states and the observations of PHMM are optimally defined according to each model using the weighted likelihood-ratio maximization (WLRM) criterion. The WLRM criterion gives high discriminability between the correct category and the incorrect categories. Therefore it gives model structures with good discriminative performance. We define the model structure combination which satisfy the WLRM criterion for any possible structure combinations as the optimal structures. A genetic algorithm is also applied to the adequate approximation of a full search. With results of continuous lecture talk speech recognition, the effectiveness of the proposed structure optimization is shown: it reduced the word errors compared to HMM and PHMM with a common structure for all models.

This paper introduces a modified particle swarm optimizer (PSO) called the Multi-Species Particle Swarm Optimizer (MSPSO) for locating all the global minima of multi-modal functions. MSPSO extend the original PSO by dividing the particle swarm spatially into a multiple cluster called a species in a multi-dimensional search space. Each species explores a different area of the search space and tries to find out the global or local optima of that area. We test our MSPSO for several multi-modal functions with multiple global optima. Our MSPSO can successfully locate all the global optima of all the test functions, and in particular, can locate all 18 global optima of the two-dimensional Shubert function. We also examined how the performance of MSPSO depends on various algorithm parameters.

This paper describes a BIST circuit for testing SoC integrated multi-channel serializer/deserializer (SerDes) macros. A newly developed packet-based PRBS generator enables the BIST to perform at-speed testing of asynchronous data transfers. In addition, a new technique for chained alignment checks between adjacent channels helps achieve a channel-count-independent architecture for verification of multi-channel alignment between SerDes macros. Fabricated in a 0.13-µm CMOS process and operating at > 500 MHz, the BIST has successfully verified all SerDes functions in at-speed testing of 5-Gbps20-ch SerDes macros.

A pitch-synchronous (PS) auditory feature extraction method based on ZCPA (Zero-Crossings Peak-Amplitudes) was proposed previously and showed more robustness over a conventional ZCPA and MFCC based features. In this paper, firstly, a non-linear adaptive threshold adjustment procedure is introduced into the PS-ZCPA method to get optimal results in noisy conditions with different signal-to-noise ratio (SNR). Next, auditory masking, a well-known auditory perception, and modulation enhancement that simulates a strong relationship between modulation spectrums and intelligibility of speech are embedded into the PS-ZCPA method. Finally, a Wiener filter based noise reduction procedure is integrated into the method to make it more noise-robust, and the performance is evaluated against ETSI ES202 (WI008), which is a standard front-end for distributed speech recognition. All the experiments were carried out on Aurora-2J database. The experimental results demonstrated improved performance of the PS-ZCPA method by embedding auditory masking into it, and a slightly improved performance by using modulation enhancement. The PS-ZCPA method with Wiener filter based noise reduction also showed better performance than ETSI ES202 (WI008).

A comparison of performances is made of three text-independent speaker identification methods based on dual Penalized Logistic Regression Machine (dPLRM), Support Vector Machine (SVM) and Gaussian Mixture Model (GMM) with experiments by 10 male speakers. The methods are compared for the speech data which were collected over the period of 13 months in 6 utterance-sessions of which the earlier 3 sessions were for obtaining training data of 12 seconds' utterances. Comparisons are made with the Mel-frequency cepstrum (MFC) data versus the log-power spectrum data and also with training data in a single session versus in plural ones. It is shown that dPLRM with the log-power spectrum data is competitive with SVM and GMM methods with MFC data, when trained for the combined data collected in the earlier three sessions. dPLRM outperforms GMM method especially as the amount of training data becomes smaller. Some of these findings have been already reported in [1]-[3].

We propose two sequence design schemes for an overloaded space-time spreading system with multiple antennas. One scheme is for a system in which the amplitude of user signals needs not be adjusted and provides tradeoffs between the user capacity and diversity order. This scheme has a certain similarity to time-sharing, but its performance is further improved by time-diversity. Another is to achieve full diversity order by varying user signal amplitudes. The diversity orders of the respective schemes are theoretically proved and their performances are demonstrated by simulation.

This letter proposes an orthogonal frequency division multiplexing (OFDM) frame synchronization scheme when the guard interval (GI) consists of a zero-padded (ZP) sequence. The frame synchronization method uses the ZP symbol where nothing is transmitted for GI so that the drop in received power can be detected to find the beginning of the frame. Simulations reveal that this method significantly improves synchronization performance of the ZP-OFDM system in a multipath fading channel.

We propose a novel simplified Viterbi equalizer for high symbol rate FWA (Fixed Wireless Access) systems carrying 64QAM signals. Reduced complexity and improved performance are achieved adopting two approaches. The first one is reducing the number of survival paths, taking advantage of the large D/U common in LOS (line of sight) communications. The second one is using a multi-stage process to generate desired signal replicas based on their likelihoods. Computer simulations confirm that the proposed replica generation method offers a performance improvement of about 1 dB and the proposed Viterbi equalizer offers reduced complexity with no performance penalty compared to full Viterbi equalizer.

We present a training algorithm to create a neural network (NN) ensemble that performs classification tasks. It employs a competitive decay of hidden nodes in the component NNs as well as a selective deletion of NNs in ensemble, thus named a pruning algorithm for NN ensembles (PNNE). A node cooperation function of hidden nodes in each NN is introduced in order to support the decaying process. The training is based on the negative correlation learning that ensures diversity among the component NNs in ensemble. The less important networks are deleted by a criterion that indicates over-fitting. The PNNE has been tested extensively on a number of standard benchmark problems in machine learning, including the Australian credit card assessment, breast cancer, circle-in-the-square, diabetes, glass identification, ionosphere, iris identification, and soybean identification problems. The results show that classification performances of NN ensemble produced by the PNNE are better than or competitive to those by the conventional constructive and fixed architecture algorithms. Furthermore, in comparison to the constructive algorithm, NN ensemble produced by the PNNE consists of a smaller number of component NNs, and they are more diverse owing to the uniform training for all component NNs.