A compact open-loop resonator bandpass filter is presented to suppress the spurious passband using compensated compact microstrip resonant cell (C-CMRC) feeding structure. Based on the inherently compact and stopband characteristics of the C-CMRC feeding, the proposed filters shows a better spurious rejection performance than the only open-loop resonator filter. The suppression is -57.4 dB, -49.5 dB, and -43.9 dB at the 2nd, 3rd and 4th harmonic signal separately. All the performance of proposed filters have been verified by the measured results.

Several research fields have to deal with very large classification problems, e.g. handwritten character recognition and speech recognition. Many works have proposed methods to address problems with large number of samples, but few works have been done concerning problems with large numbers of classes. CombNET-II was one of the first methods proposed for such a kind of task. It consists of a sequential clustering VQ based gating network (stem network) and several Multilayer Perceptron (MLP) based expert classifiers (branch networks). With the objectives of increasing the classification accuracy and providing a more flexible model, this paper proposes a new model based on the CombNET-II structure, the CombNET-III. The new model, intended for, but not limited to, problems with large number of classes, replaces the branch networks MLP with multiclass Support Vector Machines (SVM). It also introduces a new probabilistic framework that outputs posterior class probabilities, enabling the model to be applied in different scenarios (e.g. together with Hidden Markov Models). These changes permit the use of a larger number of smaller clusters, which reduce the complexity of the final classifiers. Moreover, the use of binary SVM with probabilistic outputs and a probabilistic decoding scheme permit the use of a pairwise output encoding on the branch networks, which reduces the computational complexity of the training stage. The experimental results show that the proposed model outperforms both the previous model CombNET-II and a single multiclass SVM, while presenting considerably smaller complexity than the latter. It is also confirmed that CombNET-III classification accuracy scales better with the increasing number of clusters, in comparison with CombNET-II.

This paper presents constructions of two kinds of sets of sequences with a zero correlation zone, called ZCZ code, which can reach the upper bound of the member size of the sequence set. One is a ZCZ code which can be constructed by a unitary matrix and a perfect sequence. Especially, a ternary perfect sequence with elements 1 and zero can be used to construct the proposed ZCZ code. The other is a ZCZ code of pairs of ternary sequences and binary sequences which can be constructed by an orthogonal matrix that includes a Hadamard matrix and an orthogonal sequence pair. As a special case, an orthogonal sequence pair, which consists of a ternary sequence and a binary sequence, can be used to construct the proposed ZCZ code. These codes can provide CDMA systems without co-channel interference.

A test structure to separately measure sheet resistances of highly-doped-drain (HDD) and lightly-doped-drain (LDD) in LDD-type CMOSFETs with various gate spaces S having sub-100 nm sidewalls was proposed. From the reciprocal of source/drain-resistance R-1 versus S characteristics, the sheet resistance ρH of the high-conductive-region (HCR) corresponding to HDD and the approximate width WLC of the low-conductive-region (LCR) corresponding to LDD could be estimated. Both of ρH and WLC for p- and n-MOS devices were scarcely dependent on the gate voltage. The sidewall-width difference of 40 nm could be sufficiently detected by using the test structure with the S pitch of about 60 nm. The R-1 versus S characteristics showed the unstable resistance variations in the narrow S region less than 0.3 µm, which corresponded to the minimum S for the process used for the test device fabrication and suggested that various micro-loading effects seriously affected on the characteristics.

A novel structure for a frequency-independent steerable composite right/left-handed (CRLH) leaky wave (LW) antenna in the millimeter-wave band is proposed. This has the advantages of wide beam scanning and low profile, and is a suitable structure for mass-production. The proposed antenna has features wherein a movable dielectric slab is placed above the CRLH LW antenna, and the radiation angle can be steered by changing the distance between the slab and the antenna using compact actuators. Moreover, slots are added to the antenna to control the aperture amplitude distribution of the array antenna in order to enhance aperture efficiency. A prototype CRLH LW antenna has been fabricated with these slots, and backward-to-forward beam scanning characteristics at 76 GHz have been demonstrated successfully by measurement. A wide scanning angle from 73 to 114 deg. has been achieved experimentally. The aperture efficiency is 25.3%.

In this paper, a parallel combinatory spread spectrum (PC/SS) system using a constant amplitude signaling scheme is proposed. The amplitude of the transmitted signal from multicode transmission systems such as PC/SS systems have a large dynamic range which requires that amplifiers have a wide linearity in the transmitter. From a view point of power efficiency, however, it is reasonable to use non-linear amplifiers rather than linear ones. In that case, the bit error rate performance must degrade because of non-linear distortion. The proposed system can avoid influence of the non-linear amplifiers by making the transmitted signal have a constant amplitude. The bit error rate performance and the data transmission rate performance are investigated. They prove that the proposed system is an attractive candidate among the constant amplitude signaling systems.

This paper proposes a novel pre-FFT type OFDM adaptive array antenna called "Eigenvector Combining." The eigenvector combining array antenna is a realization of a post-FFT type OFDM adaptive array antenna through a pre-FFT signal processing, so it can achieve excellent performance with less computational complexity and shorter training symbols. Numerical results demonstrate that the proposed eigenvector combining array antenna shows excellent bit error rate performance close to the lower bound just with 2 OFDM symbol-long training symbols.

This letter proposes a compensation method that can alleviate the problem of I/Q mismatch generated in the direct-conversion receiver of OFDM systems. In the proposed method, the amount of I/Q mismatch is estimated using null-carriers in transmitted signals, and it is subtracted from received symbols to suppress I/Q mismatch effects. Simulations show experiments that the proposed method can effectively eliminate the I/Q mismatch effects.

Based on the theory of block projection onto convex sets (BPOCS), a novel de-blocking algorithm is proposed. A new smoothness constraint set (SCS) is used to remove the unnecessary high frequencies. In addition, an adaptive quantization constraint set (AQCS) is employed to suppress error in the smoothing process. The proposed size and position of new SCS are different from traditional ones. Extensive experimental results are provided to demonstrate that the proposed method can achieve better image quality with fewer iterations.

We discuss a new design methodology of polynomial neural networks (PNN) in the framework of genetic algorithm (GA). The PNN is based on the ideas of group method of data handling (GMDH). Each node in the network is very flexible and can carry out polynomial type mapping between input and output variables. But the performances of PNN depend strongly on the number of input variables available to the model, the number of input variables, and the type (order) of the polynomials to each node. In this paper, GA is implemented to better use the optimal inputs and the order of polynomial in each node of PNN. The appropriate inputs and order are evolved accordingly and are tuned gradually throughout the GA iterations. We employ a binary coding for encoding key factors of the PNN into the chromosomes. The chromosomes are made of three sub-chromosomes which represent the order, number of inputs, and input candidates for modeling. To construct model by using significant approximation and generalization, we introduce the fitness function with a weighting factor. Comparisons with other modeling methods and conventional PNN show that the proposed design method offers encouraging advantages and better performance.

A highly integrated monolithic Multi-Service Transport Platform (MSTP) ASIC MSEOSX8-6 incorporating more than 26M transistors has been fabricated with 0.18 µm CMOS technology. The chip is a powerful monolithic MSTP ASIC that supports RPR applications and serves as a generic building block for MSTP network. To accelerate the chip design, we devise a novel methodology called Embedded Reduced Self-Tester (ERST), which integrates the reduced self-tester structure into the chip to shorten the duration of dynamic simulation. Moreover, we divide the design into 12 smaller Hierarchical Layout Blocks (HLB) to enable parallel layout. Resultantly, the whole design has been completed in 5 months, which saves at least 80% of the design cycle in all.

Visual criteria for diagnosing liver diseases, such as cirrhosis, from ultrasound images can be assisted by computerized texture classification. This paper proposes a system applying a PNN (Pyramid Neural Network) for classifying the hepatic parenchymal diseases in ultrasonic B-scan texture. In this study, we propose a multifractal-dimensions method to select the patterns for the training set and the validation sets. A modified box-counting algorithm is used to calculate the dimensions of the B-scan images. FDWT (Fast Discrete Wavelet Transform) is applied for feature extraction during the preprocessing. The structure of the proposed neural network is testified by training and validation sets by cross-validation method. The performance of the proposed system and a system based on the conventional multilayer network architecture is compared. The results show that, compared with the conventional 3-layer neural network, the performance of the proposed pyramid neural network is improved by efficiently utilizing the lower layer of the neural network.

A function approximation based on an orthonormal wave function expansion in a complex space is derived. Although a probability density function (PDF) cannot always be expanded in an orthogonal series in a real space because a PDF is a positive real function, the function approximation can approximate an arbitrary PDF with high accuracy. It is applied to an actor-critic method of reinforcement learning to derive an optimal policy expressed by an arbitrary PDF in a continuous-action continuous-state environment. A chaos control problem and a PDF approximation problem are solved using the actor-critic method with the function approximation, and it is shown that the function approximation can approximate a PDF well and that the actor-critic method with the function approximation exhibits high performance.

In this paper, we propose an enlargement method for images with Gaussian noise based on the Laplacian pyramid (LP) representation. Unlike lowpass pre-processing approaches to the LP enlargement method, an embedded approach is used in this paper. Since the amplitude of Gaussian noise signals is smaller than the amplitude of image edge signals in the predicted LP stage, we adopt a modified ε-filter in the proposed LP enlargement algorithm to reduce the Gaussian noise. Experimental results show that the proposed method can obtain high accuracy denoise enlarged images.

We have been investigating an orthogonal frequency division multiple access (OFDMA) based cellular system that is called "dynamic parameter controlled orthogonal frequency and time division multiple access (DPC-OF/TDMA)" for the development of beyond third generation (B3G) mobile communication systems. Moreover, we have already proposed a time alignment control (TAC) to compensate propagation delays that induce a multiple-access interference (MAI) in the uplink OFDMA. However, that TAC includes a large amount of computations. This means that it is quite difficult for the OFDMA systems to implement TAC into volume-limited hardware devices such as field programmable gate array (FPGA). Thus, we propose a new complexity-reduced TAC (CRTAC) in this paper. CRTAC can be implemented into such devices easily. In this paper, we show some computer simulation results, and then evaluate the error rate performances of DPC-OF/TDMA employing CRTAC. Moreover, we also show the benefit of the reasonable level of the implementation complexity made by CRTAC.

The optical network represents a promising approach to achieve a scalable backbone network. In backbone networks, survivability is important because high volumes of traffic are prone to be damaged by faulty equipment. Various design methods for survivable optical networks have been proposed, although none considering the simultaneous maintenance of multiple transmission lines has been proposed to our knowledge. This paper proposes a design method for survivable optical networks where multiple transmission lines sharing common transmission equipment may suffer simultaneous damage, due to failure in the transmission equipment. Moreover, two transmission lines can be maintained simultaneously. A mathematical programming model to obtain the optimum lightpath arrangement is presented assuming three kinds of lightpath recovery schemes. The relation between the required transmission line capacity and the combination pattern of two transmission lines that undergo maintenance is clarified using the proposed design method.

It is known that any chordal graph can be uniquely decomposed into simplicial components. Based on this fact, it is shown that for a given chordal graph, its automorphism group can be computed in O((c!n)O(1)) time, where c denotes the maximum size of simplicial components and n denotes the number of nodes. It is also shown that isomorphism of those chordal graphs can be decided within the same time bound. From the viewpoint of polynomial-time computability, our result strictly strengthens the previous ones respecting the clique number.

In this letter, a more exact analysis scheme for outage probability is proposed for uplink of direct sequence code division multiple access (DS-CDMA) systems. In the previous works, the effect of call admission control (CAC) on signal to interference ratio (SIR) is considered to evaluate the performance of the outage probability for CDMA systems, however, the effect of CAC on system states is not accurately considered. In this letter, we first analyze the system states more exactly by taking the effect of CAC on CDMA system states into account. Then, the exact probability of the outage is derived according to the exact system states. The probability of the system states and the outage of the proposed approximation scheme are compared with the results of the traditional analysis schemes and the computer simulation. Compared with traditional analysis schemes, the numerical results of the proposed analysis scheme is more close to the computer simulation results.

A state space compression method based on multivariate analysis was developed and applied to reinforcement learning for high-dimensional continuous state spaces. First, useful components in the state variables of an environment are extracted and meaningless ones are removed by using multiple regression analysis. Next, the state space of the environment is compressed by using principal component analysis so that only a few principal components can express the dynamics of the environment. Then, a basis of a feature space for function approximation is constructed based on orthonormal bases of the important principal components. A feature space is thus autonomously construct without preliminary knowledge of the environment, and the environment is effectively expressed in the feature space. An example synchronization problem for multiple logistic maps was solved using this method, demonstrating that it solves the curse of dimensionality and exhibits high performance without suffering from disturbance states.

To one double-breaker model, experimental investigation on blow open force was carried out. It demonstrates that the ratio between the emerging blow open force and arc power FB/ui decreases with the arcing time, the contact gap has less effect on FB/ui, and the characteristics of the blow open force are similar when the peak value of the short circuit current is beyond 4 kA. Then, according to the experimental data and conclusions, considering the influence of blow open force, the interruption process of molded case circuit breakers (MCCBs) was investigated. It demonstrates the blow open force has significant influence on interruption process and the proposed method is effective to evaluate new design of MCCBs.