This paper describes a two-dimensional clustering scheme-based analysis of audible noises induced at telephone terminals. To analyze EMI sources that cause telephone-audible noise, we use a self-organizing map, which provides a way to map high-dimensional data onto a two-dimensional domain. Also, in order to discriminate EMI sources without using particular resonance frequencies that have peaks in the frequency domain, we use the energy spectra of telephone-audible noises as input for training the self-organizing map. In applying this method in actual environments, we measured ten kinds of telephone-audible noises (due to Radio waves and cross-talk noises, etc.) and then derived their energy spectra for eight frequency bands: 1-250 Hz, 250-500 Hz, 500-1 kHz, 1 k-1.5 kHz, 1.5 k-2 kHz, 2 k-3 kHz, 3 k-4 kHz, and over 4 kHz. We visually confirmed that the measured telephone-audible noise data could be projected onto the map in accordance with their properties, resulting in a combined depiction of the composition of derived energy spectra in the frequency bands. The proposed method can deal with multi-dimensional parameters, projecting its results onto a two-dimensional space in which the projected data positions give us an effective depiction of EMI sources that cause disturbances at telephone terminals.

A self-organizing wireless network has to deal with reliability and congestion problems when the network size increases. In order to alleviate such problems, we designed and analyzed protocols and algorithms for a reliable and efficient multiple-layer self-organizing wireless network architecture. Each layer uses a high-power root node to supervise the self-organizing functions, to capture and maintain the physical topology, and to serve as the root of the hierarchical routing topology of the layer. We consider the problem of adding a new root with its own rooted spanning tree to the network. Based on minimum-depth and minimum-load metrics, we present efficient algorithms that achieve optimum selection of root(s). We then exploit layer scheduling algorithms that adapt to network load fluctuations in order to optimize the performance. For optimality we consider a load balancing objective and a minimum delay objective respectively. The former attempts to optimize the overall network performance while the latter strives to optimize the per-message performance. Four algorithms are presented and simulations were used to evaluate and compare their performance. We show that the presented algorithms have superior performance in terms of data throughput and/or message delay, compared to a heuristic approach that does not account for network load fluctuations.

Recent studies of high quality, high resolution traffic measurements have revealed that network traffic appears to be statistically self similar. Contrary to the common belief, aggregating self-similar traffic streams can actually intensify rather than diminish burstiness. Thus, traffic prediction plays an important role in network management. In this paper, Least Mean Kurtosis (LMK), which uses the negated kurtosis of the error signal as the cost function, is proposed to predict the self similar traffic. Simulation results show that the prediction performance is improved greatly over the Least Mean Square (LMS) algorithm.

We theoretically analyze the performance of coherent ultrashort light pulse code-division multiple-access (CDMA) communication systems with a nonlinear optical thresholder. The coherent ultrashort light pulse CDMA is a promising system for an optical local area network (LAN) due to its advantages of asynchronous transmission, high information security, multiple access capability, and optical processing. The nonlinear optical thresholder is based on frequency chirping induced by self-phase modulation (SPM) in optical fiber, and discriminates an ultrashort pulse from multiple access interference (MAI) with picosecond duration. The numerical results show that the thermal noise caused in a photodetector dominates the bit error rate (BER). BER decreases as the fiber length in the nonlinear thresholder and the photocurrent difference in the photodetector increase. Using the nonlinear optical thresholder allows for the response time of the photodetector to be at least 100 times the duration of the ultrashort pulses. We also show that the optimum cut-off frequency at the nonlinear thresholder to achieve the minimum BER increases with fiber length, the total number of users, and the load resistance in the photodetector.

In this paper, we propose alternate self shielding to remove critical transitions of on-chip global interconnect. Our proposed method alternates shield and signal wires cycle by cycle. The conventional self-shielding methods need additional wires to remove critical transition by encoding. The proposed alternate self-shielding, however, requires no additional wires. We evaluate our method by simulating signal transimission with a circuit simulator. As a result, our proposed method is superior in bit rate compared to others from 10% to 75%.

We have developed a 32-bit, 32-word, and 9-read, 7-write ported register file. This register file has several circuits and techniques for reducing the impact of process variation that is marked in recent process technologies, voltage variation, and temperature variation, so called PVT variation. We describe these circuits and techniques in detail, and confirm their effects by simulation and measurement of the test chip.

An efficient void filling (VF) algorithm is proposed for wavelength division multiplexing (WDM) optical packet switches (OPSes) handling variable-packet-length self-similar traffic. The computation complexity of the proposed algorithm is extremely low. We further compare the switching performance of the proposed algorithm with that of the conventional one. We demonstrate that the proposed algorithm offers significantly lower computation complexity with adequate performance.

We propose an adaptive plastic-landmine visualizing radar system employing a complex-valued self-organizing map (CSOM) dealing with a feature vector that focuses on variance of spatial- and frequency-domain inner products (V-CSOM) in combination with aperture synthesis. The dimension of the new feature vector is greatly reduced in comparison with that of our previous texture feature-vector CSOM (T-CSOM). In experiments, we first examine the effect of aperture synthesis on the complex-amplitude texture in space and frequency domains. We also compare the calculation cost and the visualization performance of V- and T-CSOMs. Then we discuss merits and drawbacks of the two types of CSOMs with/without the aperture synthesis in the adaptive plastic-landmine visualization task. The V-CSOM with aperture synthesis is found promising to realize a useful plastic-landmine detection system.

A block-matching-based self-organizing map (BMSOM) is presented. Finding a winner is carried out for each block, which is a set of neurons arranged in square. The proposed learning process updates the reference vectors of all of the neurons in a winner block. Then, the degrees of vector modifications are mainly controlled by the size (i.e., the number of neurons) of the winner block. To prevent a single cluster with neurons from splitting into some disjointed clusters, the restriction of the block size is imposed in the beginning of learning. At the main stage, this restriction is canceled. In BMSOM learning, the size of a winner block does not always decrease monotonically. The formula used to update the reference vectors is basically uncontrolled by time. Therefore, even if a map is in a nonstationary environment, training the map is probably pursued without interruption to adjust time-controlled parameters such as learning rate. Numerical results demonstrate that the BMSOM makes it possible to improve the plasticity of maps in a nonstationary environment and incremental learning.

This paper proposes a backlight module which drives multiple cold-cathode fluorescent lamps (CCFLs) with a current mirror technique to equalize the driving current for each lamp. We first adopt a half-bridge parallel-resonant inverter as the main circuit and use a single-input, multiple-output transformer to drive the multi-CCFLs. Next, we introduce current-mirror circuits to create a new current-sharing circuit, in which its current reference node and the parallel-connected multi-load nodes are used to accurately equalize all CCFLs' driving current. This will balance each lamp's brightness and, consequently, improve the picture display quality of the related liquid crystal display (LCD). This paper details the design concept for each component value with the assistance of an actual design example. The results of the example are examined with its actual measurements, which consequently verify the correctness of the proposed control strategy.

The requirement for achieving the smoothness of mode transit between track seeking and track following has become a challenging issue for hard disk drive (HDD) motion control. In this paper, a random-optimization-based self-organizing neuro-fuzzy controller (RO-SNFC) for HDD servo system is presented. The proposed controller is composed of three designs. First, the concept of pseudo-errors is used to detect the potential dynamics of the unknown plant for rule extraction. Second, the propensity of the obtained pseudo-errors is specified by a cubic regression model, with which the cluster-based self-organization is implemented to generate clusters. The generated clusters are regarded as the antecedents of the T-S fuzzy "IF-THEN" rules. The initial knowledge base of the RO-SNFC is established. Third, the well-known random optimization (RO) algorithm is used to evolve the controller parameters for control efficiency and robustness. In this paper, a motion reference curve for HDD read/write head is employed. With the reference velocity curve, the RO-SNFC is used to achieve the optimal positioning control. From the illustrations, the feasibility of the proposed approach for HDD servo systems is demonstrated. Through the comparison to other approaches, the excellent performance by the proposed approach in access time and positioning smoothness is observed.

The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process.

Multilayered filters with a dielectric distribution along their thickness forming a one-dimensional quasi-fractal structure are theoretically analyzed, focusing on exposing their resonant properties in order to understand a dielectric Menger's sponge resonator [4],[5]. "Quasi-fractal" refers to the triadic Cantor set with finite generation. First, a novel calculation method that has the ability to deal with filters with fine fractal structures is derived. This method takes advantage of Clifford algebra based on the theory of thin-film optics. The method is then applied to classify resonant modes and, especially, to investigate quality factors for them in terms of the following design parameters: a dielectric constant, a loss tangent, and a stage number. The latter determines fractal structure. Finally, behavior of the filters with perfect fractal structure is considered. A crucial finding is that the high quality factor of the modes is not due to the complete self-similarity, but rather to the breaking of such a fractal symmetry.

We show that distributed source coding of multi-view images in camera sensor networks (CSNs) using adaptive modules can come close to the Slepian-Wolf bound. In a systematic scenario with limited node abilities, work by Slepian and Wolf suggest that it is possible to encode statistically dependent signals in a distributed manner to the same rate as with a system where the signals are jointly encoded. We considered three nodes (PN, CN and CNs), which are statistically depended. Different distributed architecture solutions are proposed based on a parent node and child node framework. A PN sends the whole image whereas a CNs/CN only partially, using an adaptive coding based on adaptive module-operation at a rate close to theoretical bound - H(CNs|PN)/H(CN|PN,CNs). CNs sends sub-sampled image and encodes the rest of image, however CN encodes all image. In other words, the proposed scheme allows independent encoding and jointly decoding of views. Experimental results show performance close to the information-theoretic limit. Furthermore, good performance of the proposed architecture with adaptive scheme shows significant improvement over previous work.

We present a new method to detect weak linear frequency modulated (LFM) signals in strong noise using the chaos oscillator. Chaotic systems are sensitive to specific signals yet immune to noise. With our new method we firstly use the Radon-Wigner transform to dechirp the LFM signal. Secondly, we set up a chaotic oscillator sensitive to weak signals based on the Duffing equation, and poising the system at its critical state. Finally, we input the dechirped sequence into the system as a perturbation of the driving force. A weak signal with the same frequency will lead to a qualitative transition in the system state. The weak signal in the presence of strong noise can then be detected from the phase transition of the phase plane trajectory of the chaotic system. Computer simulation results show that LFM signals with an SNR lower than -27 dB can be detected by this method.

The authors propose a system for searching the shape of human hands and fingers in real time and with high accuracy, without using any special peripheral equipment such as range sensor, PC cluster, etc., by a method of retrieving similar image quickly with high accuracy from a large volume of image database containing the complicated shapes and self-occlusions. In designing the system, we constructed a database in a way to be adaptable even to differences among individuals, and searched CG images of hand similar to unknown hand image, through extraction of characteristics using high-order local autocorrelational patterns, reduction of the amount of characteristics centering on principal component analysis, and prior rearrangement of data corresponding to the amount of characteristics. As a result of experiments, our system performed high-accuracy estimation of human hand shape where mean error was 7 degrees in finger joint angles, with the processing speed of 30 fps or over.

Particles several tens of nanometers in size were aligned in the desired positions in a controlled manner by using capillary force interaction and suspension flow. Latex beads 40-nm in diameter were aligned linearly around a 10-µm-hole template fabricated by lithography. Further control of their position and separation was realized using colloidal gold nanoparticles by controlling the particle-substrate and particle-particle interactions using an optical near field generated on the edge of a Si wedge, in which the separation of the colloidal gold nanoparticles was controlled by the direction of polarization.

We investigated the initial stage of Zn dot growth using near-field optical chemical vapor deposition. The dependence of the rate of Zn dot deposition on dot size revealed that the deposition rate was maximal when the dot grew to a size equivalent to the probe apex diameter. Such observed size-dependent resonance was in good agreement with theoretical results for dipole-dipole coupling with a Forster field between the deposited Zn dot and the probe apex.

The explicit construction of a universal source code for correlated sources is presented. The construction is based on a technique of simulated random coding algorithms [5]. The proposed algorithm simulates the random generation of linear codes. For every pair of correlated sources whose achievable rate region includes a given pair of encoding rates, the decoding error rate of the proposed algorithm goes to zero almost surely as the block length goes to infinity.

This paper proposes two power-constrained test synthesis schemes and scheduling algorithms, under non-scan BIST, for RTL data paths. The first scheme uses boundary non-scan BIST, and can achieve low hardware overheads. The second scheme uses generic non-scan BIST, and can offer some tradeoffs between hardware overhead, test application time and power dissipation. A designer can easily select an appropriate design parameter based on the desired tradeoff. Experimental results confirm the good performance and practicality of our new approaches.