In portable applications such as W-CDMA cell phones, high performance and low standby leakage are both required. We propose an automated design technique to selectively use multi-threshold CMOS (MTCMOS) in a cell-by-cell fashion. MT cells consisting of low-Vth transistors and high-Vth sleep transistors are newly introduced. MT cells are assigned to critical paths to speed up, while High-Vth cells are assigned to non-critical paths to reduce leakage. Compared to the conventional MTCMOS, the gate delay is not affected by the discharge patterns of other gates because there is no virtual ground to be shared. We applied this technique to a test chip of a DSP core for W-CDMA baseband LSI. The worst path-delay was improved by 14% over the single high-Vth design without increasing standby leakage at 10% area overhead.

Scanning near-field optical microscopy (SNOM) combined with Kelvin force microscopy (KFM) using a microfabricated force-sensing cantilever with a lead zirconate titanate (PZT) thin film as an integrated deflection sensor have been developed. We applied the frequency modulation (FM) detection method to this setup to increase the detection sensitivity of electrostatic forces between a probe tip and a sample. Latex particles dispersed in a polyvinylalcohol (PVA) thin film deposited onto a glass substrate were stably imaged with the SNOM while both local optical and electrical properties of a ferroelectric thin film were successfully investigated.

Adaptive beamforming, using the Conjugate Gradient Normal Equation Residual problem, is applied to a base station array, in the UTRA-TDD up-link. A Wideband Directional Channel Model is used, characterising specific micro-cell, street-type scenarios. These differ in the number of mobile terminals, grouped and placed along the street axis, and on their distances to the base station. Time- and angle-of-arrival spreads, and on-the-air interference content are the main parameters inherently varied and analysed. The average beamforming gain and signal-to-noise ratio are evaluated, also varying the number of array elements. The high number of arriving correlated and closely correlated signals, together with the composed nature of the correlation matrix in the algorithm's cost function, result in that other than the MMSE solutions may lead to the best interference suppression, for the tested scenarios. Among the several weighted interfering power components, the most relevant is due to the delayed signals from all the other links. The combination of the number of arriving orthogonal codes, time-of-arrival and angle-of-arrival spreads condition beamforming performance: the number of array elements affect performance, depending on the mobile terminal distance to the base station, and on the number of active links; for short distances and large number of users, larger time-of-arrival spread degrades beamformer performance, over the opposing effect of angle-of-arrival spread; the number of active users affects beamforming gain especially in the case that delay spreads are larger, i.e., for shorter mobile terminal distances to the base station.

In this paper, an associative memory model with a forgetting process proposed by Mezard et al. is investigated as a means of storing sparsely encoded patterns by the SCSNA proposed by Shiino and Fukai. Similar to the case of storing non-sparse (non-biased) patterns as analyzed by Mezard et al., this sparsely encoded associative memory model is also free from a catastrophic deterioration of the memory caused by memory pattern overloading. We theoretically obtain a relationship between the storage capacity and the forgetting rate, and find that there is an optimal forgetting rate leading to the maximum storage capacity. We call this the optimal storage capacity rate. As the memory pattern firing rate decreases, the optimal storage capacity increases and the optimal forgetting rate decreases. Furthermore, we shown that the capacity rate (i.e. the ratio of the storage capacity for the conventional correlation learning rule to the optimal storage capacity) is almost constant with respect to the memory pattern firing rate.

In this paper, we study a low profile top loaded monopole antenna. By changing the number, thickness, position and shape of post(s), the input and radiation characteristic due to parameters of matching post(s) are investigated. The low profile top loaded monopole antenna (TLMA) is known as a suitable way for antenna's miniaturization. But it is also reported that the parameters of matching post influence the input and radiation characteristic greatly. The FDTD method is well suit for use in analyzing both the plate and wire structure. And to improve the calculation effect efficiency, the non-uniform mesh FDTD algorithm is used. From the measurement and simulation results, we propose the most suitable parameters of matching structure for low profile top loaded monopole antenna.

This paper proposes a new blind adaptive algorithm for computing the weight vector of an antenna array system. The new technique utilizes a Generalized On-Off algorithm to obtain the weight vector from the pilot channel of IS2000 1X system, of which the processing gain can be controlled arbitrarily. The proposed algorithm generates a suboptimal weight vector maximizing the SINR (signal to interference plus noise ratio) with a linear computational load. Based on the analysis obtained from various simulations, it is observed that the proposed algorithm is suitable for the practical IS2000 1X mobile communication environments.

This paper presents a flexible learning algorithm for the binary neural network that can realize a desired Boolean function. The algorithm determines hidden layer parameters using a genetic algorithm. It can reduce the number of hidden neurons and can suppress parameters dispersion. These advantages are verified by basic numerical experiments.

In this letter, our proposed approach exploits the use of original and simplest Cellular Neural Network (CNN) for 2D Doubly Complementary (DC) Infinite Impulse Response (IIR) filter banks design. The properties of feedback and feedforward templates are studied for this purpose. Through some examples it is shown how generalizations of these templates can be used for DC IIR filter banks design. We modify Lagrangian function which is used for optimizing a low-pass filter design considering the constraint for stability of CNN. The brief conclusions with design examples that illustrate the proposed method and an image enhancement and restoration applications of designed filter banks are presented.

This letter presents a new approximation algorithm suitable for Taylor series expansion. The algorithm can effectively reduce the approximation error by using only a small number of terms in series expansion. The proposed algorithm can be more easily implemented and has better performance than the conventional Euler approximation algorithm. Also, the approximation performance of the proposed algorithm is compared with direct approaches, such as least-squares and Chebyshev approximation algorithm to show the relative advantages of the proposed algorithm. This letter also presents an application example of the proposed approximation algorithm in carrier recovery of OFDM (Orthogonal Frequency Division Multiplexing) modem.

Interoperability between different systems is becoming a more important issue for open distributed systems. In this paper, we investigate what kind of framework we need for constructing open distributed systems. Firstly, we enumerate the features and functions which the framework should have. We then evaluate a proposed multi-agent framework, Bee-gent, by using a typical example of open distributed systems. Lastly, we show clearly what is required for such a framework.

Recently, Lin et al. addressed two weaknesses of a new strong-password authentication scheme, the SAS protocol, and then proposed an improved one called the OSPA (Optimal Strong-Password Authentication) protocol. However, we find that both the OSPA protocol and the SAS protocol are vulnerable to the stolen-verifier attack.

Autonomous distributed manufacturing systems (ADMS) consist of multiple intelligent components with each component acting according to its own judgments. The ADMS objective is to realize more agile and adaptive manufacturing systems. This paper presents the introduction of context-dependent agents (CDAs) in ADMS that switch strategies depending on system conditions to achieve better performance than can be realized by agents that use the same strategies under all system conditions. For the real-time job scheduling problem, the paper presents a basic CDA architecture and the results of an extensive empirical evaluation of its performance relative to other rule-based schemes based on several common indices for real-time dispatch.

The present study introduces the adaptive BPF to the BPSK coherent detection system and the characteristic of the resulting system is investigated.

This paper presents efficient file management of a hard disk drive embedded digital satellite receiver. The digital broadcasting technology enables multimedia access via broadcasting systems. The amount of digital data to be processed is increased remarkably as compared to the previous analog broadcasting environments. The efficient digital data storage and management technology are discussed in this paper to cope with these changes. The DSR uses a new file system that is designed by considering disk cluster sizes and limited memories in the system, which is more appropriate than that of general Personal Computers. The proposed system enables us to watch broadcasting and to manage multimedia data efficiently.

The one-sample locally optimum rank detector test statistics for composite signals in multiplicative and signal-dependent noise are obtained. Since the one-sample locally optimum rank detector makes use of the sign statistics of observations as well as the rank statistics, both 'even' and 'odd' score functions have to be considered. Although the one-sample locally optimum rank detector requires two score functions while the two-sample detector requires only one score function, the one-sample detector requires fewer calculations since it has to rank fewer observations.

A siphon-trap of a Petri net N is defined as a place set S with S = S, where S = { u| N has an edge from u to a vertex of S} and S = { v| N has an edge from a vertex of S to v}. A minimal siphon-trap is a siphon-trap such that any proper subset is not a siphon-trap. The following polynomial-time algorithms are proposed: (1) FDST for finding, if any, a minimal siphon-trap or even a maximal class of mutually disjoint minimal siphon-traps of a given Petri net; (2) FDSTi that repeats FDST i times in order to extract more minimal siphon-traps than FDST. (3) STFM_T (STFM_Ti, respectively) which is a combination of the Fourier-Motzkin method and FDST (FDSTi) and which has high possibility of finding, if any, at least one minimal-support nonnegative integer invariant.

A novel adaptive technique based on a statistical model by estimating window size for unsupervised segmentation of a set of MR images is presented. The window size estimation is achieved in the image using a MDL for mixture estimation and segmentation, and allows the technique to well reflect local characteristics of the image.

In this paper, we clarify the properties of the contract net protocol based on its formal specification. To specify the contract net protocol, we propose a formal specification method for an agent system. In this method, agents are modeled as communicating finite state machines. To deal with the behavior of agents and its time passage explicitly, we incorporate the concept of time into the communicating finite state machine. The contract net protocol is specified based on the specification method proposed in this paper. From the specification, we analyze the possibility about agent deadlock and its avoidance solution.

An efficient algorithm is proposed for finding all dc solutions of piecewise-linear (PWL) circuits. This algorithm is based on a powerful test (termed the LP test) for nonexistence of a solution to a system of PWL equations in a given region using the dual simplex method. The proposed algorithm also uses a special technique that decreases the number of regions on which the LP test is performed. By numerical examples, it is shown that the proposed algorithm could find all solutions of large scale problems, including those where the number of variables is 500 and the number of linear regions is 10500, in practical computation time.

The two-sample locally optimum rank detector test statistics for composite signals in additive, multiplicative, and signal-dependent noise are obtained in this letter. Compared with the structure of the one-sample locally optimum rank detector, that of the two-sample locally optimum rank detector is shown to be simpler, although it needs more computations. It is known that there is a trade-off of computational complexity and structural simplicity between the one- and two-sample detectors.