This paper proposes a novel channel estimation method for iterative equalization in MIMO systems. The proposed method incorporates co-channel interference (CCI) cancellation in the channel estimator and the channel estimation is successively performed with respect to each stream. Accuracy of channel estimation holds the key to be successfully converged the iterative equalization and decoding process. Although the channel estimates can be re-estimated by means of LS (Least Square) channel estimation using tentative decisions obtained in the iterative process, its performance is severely limited in a MIMO system because of erroneous decisions and ill-conditioned channel estimation matrix. The proposed method can suppress the above effects by means of CCI cancellation and successive channel estimation. Computer simulation confirms that the proposed channel estimation method can accurately estimate the channel, and the receiver with iterative equalization and the proposed method achieves excellent decoding performance in a MIMO-SM system.

The dependences of the structural, optical and electrical properties of highly transparent conductive Ga-doped ZnO (GZO) films on thickness have been studied. GZO films were prepared on unheated glass, polymethyl methacrylate (PMMA) and cyclo olefin polymer (COP) substrates by ion plating deposition with direct-current arc discharge. Polycrystalline GZO films with good adherence to a substrate having a (0002) preferred orientation have been obtained. Very little difference was found between the resistivity values of the GZO films on the glass substrate and those of the GZO films on the different polymer substrates, at any given film thickness. On both plastic substrates, the resistivity of the GZO films decreased from 210- 3 to 510-4 Ωcm with increasing film thickness.

Multipath energy capture and inter-symbol interference (ISI) are two intractable problems in high-data-rate Ultra-wideband (UWB) systems. To tackle the problems and simplify the receiver, we propose an adaptive interference avoidance scheme based on Pre-RAKE combining technique. The symbol repetition period (SRP) is regarded a changeable parameter in an ordered set to avoid severe interference paths and guarantee high data-rate. The set is known to both the transmitter and receiver. The index of the selected SRP is then sent to the receiver to coordinate the transmitter and receiver. The SRP can be updated adaptively according to the variations of the channels. Both theoretical analysis and simulations show that the ISI is mitigated and the transmission rate is improved simultaneously compared to the constant SRP transmission scheme.

We report effects of washing rubbed polyimide film on the near surface. Especially we focused dependence of solvent. Rubbed polyimide films have been used as liquid crystal alignment films in Liquid crystal displays (LCDs), and in actual LCD panel fabrication washing on film surfaces after rubbing is essential process to remove dust and pollution. We investigated the effects of washing by grazing incidence X-ray diffraction (GIXD) measurements. In GIXD, the X-ray penetration into the polymer was changed from 8 nm (suface sensitive) to 4 nm (bulk sensitive) by variation of the X-ray incidence angle. It was found that crystallization near the surface induced by soaking was considerably dependent on solvent. However, in-plane distribution of the surface polymer chains of polyimide film was not found to be dependent on the solvents.

This paper presents a text-independent speaker verification method using Gaussian mixture models (GMMs), where only utterances of enrolled speakers are required. Artificial cohorts are used instead of those from speaker databases, and GMMs for artificial cohorts are generated by changing model parameters of the GMM for a claimed speaker. Equal error rates by the proposed method are about 60% less than those by a conventional method which also uses only utterances of enrolled speakers.

With the ubiquitous application of Internet and wireless networks, H.264 video communication becomes more and more common. However, due to the high-efficiently predictive coding and the variable length entropy coding, it is more sensitive to transmission errors. The current error concealment (EC) scheme, which utilizes the spatial and temporal correlations to conceal the corrupted region, produces unsatisfied boundary artifacts. In this paper, first we propose variable block size error concealment (VBSEC) scheme inspired by variable block size motion estimation (VBSME) in H.264. This scheme provides four EC modes and four sub-block partitions. The whole corrupted macro-block (MB) will be divided into variable block size adaptively according to the actual motion. More precise motion vectors (MV) will be predicted for each sub-block. Then MV refinement (MVR) scheme is proposed to refine the MV of the heterogeneous sub-block by utilizing three step search (TSS) algorithm adaptively. Both VBSEC and MVR are based on our directional spatio-temporal boundary matching algorithm (DSTBMA). By utilizing these schemes, we can reconstruct the corrupted MB in the inter frame more accurately. The experimental results show that our proposed scheme can obtain better objective and subjective EC quality, respectively compared with the boundary matching algorithm (BMA) adopted in the JM11.0 reference software, spatio-temporal boundary matching algorithm (STBMA) and other comparable EC methods.

The frequency domain binaural model (FDBM) has been previously proposed to localize multiple sound sources. Since the method requires only two input signals and uses interaural phase and level differences caused by the diffraction generated by the head, flexibility in application is very high when the head is considered as an object. When an object is symmetric with respect to the two microphones, the performance of sound source localization is degraded, as a human being has front-back confusion due to the symmetry in a median plane. This paper proposes to reduce the degradation of performance on sound source localization by a combination of the microphone pair outputs using the FDBM. The proposed method is evaluated by applying to a security camera system, and the results showed performance improvement in sound source localization because of reducing the number of cones of confusion.

This paper describes a method for recognizing romanized Japanese words in learner English. They become noise and problematic in a variety of systems and tools for language learning and teaching including text analysis, spell checking, and grammatical error detection because they are Japanese words and thus mostly unknown to such systems and tools. A problem one encounters when recognizing romanized Japanese words in learner English is that the spelling rules of romanized Japanese words are often violated. To address this problem, the described method uses a clustering algorithm reinforced by a small set of rules. Experiments show that it achieves an F-measure of 0.879 and outperforms other methods. They also show that it only requires the target text and an English word list of reasonable size.

Embedded zero-tree image coding in wavelet domain has drawn a lot of attention. Among noteworthy algorithms is the set partitioning in hierarchical trees (SPIHT). Typically, most of images' energy is concentrated in low frequency subbands. For an image with textures, however many middle-high frequency wavelet coefficients are likely to become significant in the early passes of SPIHT; thus the coding results are often insufficient. Middle and high frequency subbands of images may demand further decompositions using adaptive basis functions. As wavelet packet transform offers a great diversity of basis functions, we propose a quad-tree based adaptive wavelet packet transform to construct adaptive wavelet packet trees for zero-tree image coding. Experimental results show that coding performances can be significantly improved especially for fingerprints images.

Clustering is indispensable to obtain a general view of series data from a number of data such as gene expression profiles. We propose a novel metric for clustering. The proposed metric automatically normalizes data to minimize a logarithmic scale distance between the data series.

Programmable Metallization Cell (PMC) Random Access Memory is based on the electrochemical growth and removal of nanoscale metallic pathways in thin films of solid electrolytes. In this study, we investigate the nature of thin films formed by the photo doping of Cu into chalcogenide materials for use in programmable metallization cell devices. These devices rely on metal ion transport in the film so produced to create electrically programmable resistance states. The results imply that a Cu-rich phase separates owing to the reaction of Cu with free atoms from chalcogenide materials.

In this paper, two new clustering algorithms based on fuzzy c-means for data with tolerance using kernel functions are proposed. Kernel functions which map the data from the original space into higher dimensional feature space are introduced into the proposed algorithms. Nonlinear boundary of clusters can be easily found by using the kernel functions. First, two clustering algorithms for data with tolerance are introduced. One is based on standard method and the other is on entropy-based one. Second, the tolerance in feature space is discussed taking account into soft margin algorithm in Support Vector Machine. Third, two objective functions in feature space are shown corresponding to two methods, respectively. Fourth, Karush-Kuhn-Tucker conditions of two objective functions are considered, respectively, and these conditions are re-expressed with kernel functions as the representation of an inner product for mapping from the original pattern space into a higher dimensional feature space. Fifth, two iterative algorithms are proposed for the objective functions, respectively. Through some numerical experiments, the proposed algorithms are discussed.

This paper presents a distributed approach for adaptive flocking of swarms of mobile robots that enables to navigate autonomously in complex environments populated with obstacles. Based on the observation of the swimming behavior of a school of fish, we propose an integrated algorithm that allows a swarm of robots to navigate in a coordinated manner, split into multiple swarms, or merge with other swarms according to the environment conditions. We prove the convergence of the proposed algorithm using Lyapunov stability theory. We also verify the effectiveness of the algorithm through extensive simulations, where a swarm of robots repeats the process of splitting and merging while passing around multiple stationary and moving obstacles. The simulation results show that the proposed algorithm is scalable, and robust to variations in the sensing capability of individual robots.

Autonomous Decentralized Community System (ADCS) makes its basis on offering customized and dynamic services to group of end-users having common preferences at specified time and location. Owing to extreme dynamism in the system caused by rapidly varying user's demands, and severe mobility of users, it is quite difficult to assure timely service provision to all community members. This paper presents autonomous decentralized community system construction by autonomous division and integration technologies to procure service assurance under dynamic situations, without involving significant communication overhead. By adopting the concept of size threshold, the proposed technique continuously maintains the appropriate size of community in constantly and rapidly changing operating environment, to deliver optimal quality of service in terms of response time. The effectiveness of proposed technology has been shown through simulation, which reveals remarkable improvement (up to 29%) in response time.

This paper proposes a combination of novel Received Response (RR) sequence at the transmitter and Matched Filter-Equalizer-RAKE (MF-EQZ-RAKE) combining scheme receiver system for Direct Sequence-Ultra Wideband (DS-UWB) multipath channel model. When binary code sequence such as M sequence is used, there is a possibility of generating extra Inter-Symbol Interference (ISI) in the UWB system. Therefore, it is quite a challenging task to collect the energy efficiently although RAKE reception method is applied at the receiver. The main purpose of the proposed system is to overcome the performance degradation for UWB transmission due to the occurrence of Inter-Symbol Interference (ISI) during high speed transmission of ultra short pulses in a multipath channel. The proposed system improves the system performance by improving the RAKE reception performance using RR sequence and suppressing the ISI effect with the equalizer. Simulation results verify that significant improvement can be obtained by the proposed system especially in UWB multipath channel models such as channel CM4 that suffered severe ISI effect.

In direct-sequence code-division multiple-access (DS-CDMA) communication systems and direct-sequence ultra wideband (DS-UWB) radios, sequences with low correlation and large family size are important for reducing multiple access interference (MAI) and accepting more active users, respectively. In this paper, a new collection of families of sequences of length pn-1, which includes three constructions, is proposed. The maximum number of cyclically distinct families without GMW sequences in each construction is , where p is a prime number, n is an even number, and n=2m, and these sequences can be binary or polyphase depending upon choice of the parameter p. In Construction I, there are pn distinct sequences within each family and the new sequences have at most d+2 nontrivial periodic correlation {-pm-1,-1,pm-1,2pm-1,,dpm-1}. In Construction II, the new sequences have large family size p2n and possibly take the nontrivial correlation values in {-pm-1,-1,pm-1,2pm-1,,(3d-4)pm-1}. In Construction III, the new sequences possess the largest family size p(d-1)n and have at most 2d correlation levels {-pm-1,-1,pm-1,2pm-1,,(2d-2)pm-1}. Three constructions are near-optimal with respect to the Welch bound because the values of their Welch-Ratios are moderate, WR d, WR 3d-4 and WR 2d-2, respectively. Each family in Constructions I, II and III contains a GMW sequence. In addition, Helleseth sequences and Niho sequences are special cases in Constructions I and III, and their restriction conditions to the integers m and n, pm≠ 2(mod 3) and n≡ 0 (mod 4), respectively, are removed in our sequences. Our sequences in Construction III include the sequences with Niho type decimation 32m-2, too. Finally, some open questions are pointed out and an example that illustrates the performance of these sequences is given.

Sensor node localization is an important issue in wireless sensor networks (WSNs) due to the dynamic nature of sensor deployment. Generally, in wireless sensor network localization, the absolute positions of certain anchor nodes are required based on the use of global positioning systems, then all the other nodes are approximately localized using various algorithms based on a coordinate system of the anchors. This paper proposes a neighbor position-based localization algorithm (NPLA) that can greatly enhance the positioning accuracy when compared with current overlapping connectivity localization algorithms that attempt to use the observation of connectivity to a set of anchors to determine a node's position. The proposed method localizes the sensor nodes using both the anchors' positions and neighbor node information. However, unlike existing overlapping-based methods, the proposed NPLA does not assume the same radio transmission range. A simulation study is used to demonstrate the positioning accuracy of the proposed method with different anchor and sensor node densities.

The passive and sparse reduced-order modeling of a RLC network is presented, where eigenvalues and eigenvectors of the original network are used, and thus the obtained macromodel is more accurate than that provided by the Krylov subspace methods or TBR procedures for a class of circuits. Furthermore, the proposed method is applied to low pass filtering of a reduced-order model produced by these methods without breaking the passivity condition. Therefore, the proposed eigenspace method is not only a reduced-order macromodeling method, but also is embedded in other methods enhancing their performances.

The task of joint channel and data estimation based on the maximum likelihood principle is addressed using a continuous and discrete particle swarm optimization (PSO) algorithm over additive white Gaussian noise channels. The PSO algorithm works at two levels. At the upper level continuous PSO estimates the channel while at the lower level, discrete PSO detects the data. Simulation results indicate that under the same conditions, PSO outperforms the best of the published alternatives.

We propose here a fully Spice-oriented design algorithm of op-amps for attaining the maximum gains under low power consumptions and assigned slew-rates. Our optimization algorithm is based on a well-known steepest descent method combining with nonlinear programming. The algorithm is realized by equivalent RC circuits with ABMs (analog behavior models) of Spice. The gradient direction is decided by the analysis of sensitivity circuits. The optimum parameters can be found at the equilibrium point in the transient response of the RC circuit. Although the optimization time is much faster than the other design tools, the results might be rough because of the simple transistor models. If much better parameter values are required, they can be improved with Spice simulator and/or other tools.