An adaptive array antenna for the suppression of high-power interference in direct-sequence code-division multiple access (DS-CDMA) systems is presented. Although DS-CDMA has sufficient flexibility to support a variety of services, from voice to moving-pictures, with high levels of quality, multiple access interference (MAI) is a problem. This is particularly so of the high-power interference which accompanies high-speed transmission in DS-CDMA. While the application of adaptive array antennas is an effective way of improving signal-to-interference-plus-noise ratio (SINR), problems with this approach include large levels of power consumption and the high costs of hardware and of implementing the antennas. Therefore, our main purpose is to realize a simple configuration for an adaptive array system. In order to reduce the required amounts of processing, a common beam provides suppression of high-power interference for the low-bit-rate users; this makes per-user preparation of weights unnecessary. This approach also reduces the consumption of power by the system. Interference is cancelled by minimization of the array output power (i.e., the application of a power inversion algorithm) before despreading. The approach also allows us to improve the implementation of the antenna elements by using small auxiliary antennas. The basic performance of the system is confirmed through numerical calculation and computer simulation. Furthermore, a real-time processing unit has been developed and the effectiveness of the approach is confirmed by an experiment in a radio-anechoic chamber.

New algorithms for the soft-decision and the hard-decision maximum likelihood decoding (MLD) for binary linear block codes are proposed. It has been widely known that both MLD can be regarded as an integer programming with binary arithmetic conditions. Recently, Conti and Traverso have proposed an efficient algorithm which uses Grobner bases to solve integer programming with ordinary integer arithmetic conditions. In this paper, the Conti-Traverso algorithm is extended to solve integer programming with modulo arithmetic conditions. We also show how to transform the soft-decision and the hard-decision MLD to integer programming for which the extended Conti-Traverso algorithm is applicable.

In this work it is shown for the first time how to calculate in advance by momentum-based noise simulation for stationary Monte Carlo (MC) device simulations the CPU time, which is necessary to achieve a predefined error level. In addition, analytical expressions for the simulation-time factor of terminal current estimation are given. Without further improvements of the MC algorithm MC simulations of small terminal currents are found to be often prohibitively CPU intensive.

In this work, we review our recent efforts to make effective use of atomistic calculations for the advancement of VLSI process simulation. We focus on three example applications: the behavior of implanted fluorine, arsenic diffusion and activation, and the impact of charge interactions on doping fluctuations.

This paper proposes a silence compression algorithm operating at multi-rates (MR) and with dual-bandwidths (DB), a narrowband and a wideband, for the MPEG (Moving Picture Experts Group)-4 CELP (Code Excited Linear Prediction) standard. The MR/DB operations are implemented by a Variable-Frame-size/Dual-Bandwidth Voice Activity Detection (VF/DB-VAD) module with bandwidth conversions of the input signal, and a Variable-Frame-size Comfort Noise Generator (VF-CNG) module. The CNG module adaptively smoothes the Root Mean Square (RMS) value of the input signal to improve the coding quality during transition periods. The algorithm also employs a Dual-Rate Discontinuous Transmission (DR-DTX) module to reduce an average transmission bitrate during silence periods. Subjective test results show that the proposed silence compression algorithm gives no degradation in coding quality for clean and noisy speech signals. These signals include about 20 to 30% non-speech frames and the average transmission bitrates are reduced by 20 to 40%. The proposed algorithm has been adopted as a part of the ISO/IEC MPEG-4 CELP version 2 standard.

This paper presents a group theoretic approach to the design of Decision diagrams (DDs) with increased functionality of nodes. Basic characteristics of DDs determine their applications, and thus, the optimization of DDs with respect to different characteristics is an important task. Increased functionality of nodes provides for optimization of DDs. In this paper, the methods for optimization of binary DDs by pairing of variables are interpreted as the optimization of DDs by changing the domain group for the represented functions. Then, it is pointed out that, for Abelian groups, the increased functionality of nodes by using larger subgroups may improve some of the characteristics of DDs at the price of other characteristics. With this motivation, we proposed the use of non-Abelian groups for the domain of represented functions by taking advantages from basic features of their group representations. At the same time, the present methods for optimization of DDs, do not offer any criterion or efficient algorithm to choose among a variety of possible different DDs for an assumed domain group. Therefore, we propose Fourier DDs on non-Abelian groups to exploit the reduced cardinality of the Fourier spectrum on these groups.

The implant-anneal cycle for B doping during Si device fabrication causes transient enhanced diffusion (TED) of B and the formation of small immobile B-interstitial clusters (BICs) which deactivate the B. Additionally, since modern ultrashallow devices put most of the B in immediate proximity of the Si/SiO2 interface, interface-dopant interactions like segregation become increasingly important. In this work, we use density-functional theory calculations to study TED, clustering, and segregation of B during annealing and discuss a continuum model which combines the TED and clustering results.

A new analysis method for random dopant induced threshold voltage fluctuations by using Monte Carlo ion implantation were presented. The method was applied to investigate Vt fluctuations due to statistical variation of pocket dopant profile in 0.1µm MOSFET's by 3D process-device simulation system. This method is very useful to analyze a statistical fluctuation in sub-100 nm MOSFET's efficiently.

This paper describes high-quality and processor-efficient software implementation of an MPEG-2 AAC LC Profile encoder. MDCT and quantization processing are accelerated by 21.3% and 19.0%, respectively, through the use of SIMD instructions. In addition, psycho-acoustic analysis in the MDCT domain makes the use of FFTs unnecessary and reduces the computational cost of the analysis by 56.0%. The results of subjective quality tests show that better sound quality is provided by greater efficiency in quantization processing and Huffman coding. All of this results in high-quality and processor-efficient software implementation of an MPEG-2 AAC encoder. Subjective test results show that the sound quality achieved at 96 kb/s/stereo is equivalent to that of MP3 at 128 kb/s/stereo. The encoder works 13 times faster than realtime for stereo encoding on an 800 MHz Pentium III processor.

This paper concerns recognizing 3-dimensional object using proposed multi-layer block model. In particular, we aim to achieve desirable recognition performance while restricting the computational load to a low level using 3-step feature extraction procedure. An input image is first precisely partitioned into hierarchical layers of blocks in the form of base blocks and overlapping blocks. The hierarchical blocks are merged into a matrix, with which abundant local feature information can be obtained. The local features extracted are then employed by the kernel based support vector machines in tournament for enhanced system recognition performance while keeping it to low dimensional feature space. The simulation results show that the proposed feature extraction method reduces the computational load by over 80% and preserves the stable recognition rate from varying illumination and noise conditions.

In this letter, we study the performance of the iterative receiver as applied to the space division multiplexing/orthogonal frequency division multiplexing (SDM/OFDM) systems. The iterative receiver under consideration employs the soft in/soft out (SISO) decoding process, which operates iteratively in conjunction with channel estimation for performing data detection and channel estimation at the same time. As opposed to the previous studies in which the perfect channel state information is assumed, the effects of channel estimation are taken into account for evaluating the performance of the iterative receiver and it is shown that the channel estimation applied in every iteration step of the iterative receiver plays a crucial role to warrant the performance, especially at a low signal-to-noise power ratio (SNR).

This paper describes a new context clustering technique for average voice model, which is a set of speaker independent speech synthesis units. In the technique, we first train speaker dependent models using multi-speaker speech database, and then construct a decision tree common to these speaker dependent models for context clustering. When a node of the decision tree is split, only the context related questions which are applicable to all speaker dependent models are adopted. As a result, every node of the decision tree always has training data of all speakers. After construction of the decision tree, all speaker dependent models are clustered using the common decision tree and a speaker independent model, i.e., an average voice model is obtained by combining speaker dependent models. From the results of subjective tests, we show that the average voice models trained using the proposed technique can generate more natural sounding speech than the conventional average voice models.

Accurate estimation of accentual attribute values of words, which is required to apply rules of Japanese word accent sandhi to prosody generation, is an important factor to realize high-quality text-to-speech (TTS) conversion. The rules were already formulated by Sagisaka et al. and are widely used in Japanese TTS conversion systems. Application of these rules, however, requires values of a few accentual attributes of each constituent word of input text. The attribute values cannot be found in any public database or any accent dictionaries of Japanese. Further, these values are difficult even for native speakers of Japanese to estimate only with their introspective consideration of properties of their mother tongue. In this paper, an algorithm was proposed, where these values were automatically estimated from a large amount of data of accent types of accentual phrases, which were collected through a long series of listening experiments. In the proposed algorithm, inter-speaker differences of knowledge of accent sandhi were well considered. To improve the coverage of the estimated values over the obtained data, the rules were tentatively modified. Evaluation experiments using two-mora accentual phrases showed the high validity of the estimated values and the modified rules and also some defects caused by varieties of linguistic expressions of Japanese.

Compatibility of conventional lossless discrete cosine transforms (LDCTs) with the discrete cosine transform (DCT) is not high due to rounding operations. In this paper, we design an LDCT which has high compatibility with the DCT. We first design an 8-point DCT (DCT3) by changing the order of row of the transform matrix and also the way of decomposing the DCT in order to obtain an 8-point LDCT which has high compatibility with the DCT. Next we design an 88-point nonseparable 2D LDCT based on a 4-point lossless Walsh-Hadamard Transform (LWHT) which is multiplier-free. The DCT3 is used, when the nonseparable 2D LDCT is designed. Simulation results show that compatibility of the nonseparable 2D LDCT with the separable 2D DCT is high. We also design an 88-point nonseparable 2D LWHT which is multiplier-free and indicate that its compatibility with the separable 2D Walsh-Hadamard Transform is high.

We propose herein a motion detection artificial vision model which uses analog electronic circuits. The proposed model is comprised of four layers. The first layer is a differentiation circuit of the large CR coefficient, and the second layer is a differentiation circuit of the small CR coefficient. Thus, the speed of the movement object is detected. The third layer is a difference circuit for detecting the movement direction, and the fourth layer is a multiple circuit for detecting pure motion output. When the object moves from left to right the model outputs a positive signal, and when the object moves from right to left the model outputs a negative signal. We first designed a one-dimensional model, which we later enhanced to obtain a two-dimensional model. The model was shown to be capable of detecting a movement object in the image. Using analog electronic circuits, the number of connections decrease and real-time processing becomes feasible. In addition, the proposed model offers excellent fault tolerance. Moreover, the proposed model can be used to detect two or more objects, which is advantageous for detection in an environment in which several objects are moving in multiple directions simultaneously. Thus, the proposed model allows practical, cheap movement sensors to be realized for applications such as the measurement of road traffic volume or counting the number of pedestrians in an area. From a technological viewpoint, the proposed model facilitates clarification of the mechanism of the biomedical vision system, which should enable design and simulation by an analog electric circuit for detecting the movement and speed of objects.

We propose two simple algorithms based on bounded tickets for the mutual exclusion problem on the asynchronous single-writer/multi-reader shared memory model. These algorithms are modifications of the Bakery algorithm. An unattractive property of the Bakery algorithm is that the size of its shared memory is unbounded. Initially we design a provisional algorithm based on bounded tickets. It guarantees mutual exclusion in the case where a certain condition is satisfied. To remove the condition, we use an additional process that does not correspond to any user. The algorithm with the additional process is a lockout-free mutual exclusion algorithm on the asynchronous single-writer/multi-reader shared memory model. We then modify this algorithm to reduce the shared memory size with the cost of using another additional process. The maximum waiting time using each of the algorithms proposed in this paper is bounded by (n-1)c+O(nl), where n is the number of users, l is an upper bound on the time between two successive atomic steps, and c is an upper bound on the time that any user spends using the resource. The shared memory size needed by the first algorithm and the second algorithm are (n+1)(1+log (4n)) bits and n(1+log (4n-4))+2 bits, respectively.

In this paper, we consider two types of promises for (k-)CNF formulas which can help to find a satisfying assignment of a given formula. The first promise is the Hamming distance between truth assignments. Namely, we know in advance that a k-CNF formula with n variables, if satisfiable, has a satisfying assignment with at most pn variables set to 1. Then we ask whether or not the formula is satisfiable. It is shown that for k 3 and (i) when p=nc (-1 < c 0), the problem is NP-hard; and (ii) when p=log n/n, there exists a polynomial-time deterministic algorithm. The algorithm is based on the exponential-time algorithm recently presented by Schoning. It is also applied for coloring k-uniform hypergraphs. The other promise is the number of satisfying assignments. For a CNF formula having 2n/2nε (0 ε < 1) satisfying assignments, we present a subexponential-time deterministic algorithm based on the inclusion-exclusion formula.

This paper investigates properties of space-bounded "two-dimensional Turing machines (2-tm's)," whose input tapes are restricted to square ones, with bounded input head reversals in vertical direction. We first investigate a relationship between determinism and nondeterminism for space-bounded and input head reversal-bounded 2-tm's. We then investigate how the number of input head reversals affects the accepting power of sublinearly space-bounded 2-tm's. Finally, we investigate necessary and sufficient spaces for three-way 2-tm's to simulate four-way two-dimensional finite automata with constant input head reversals.

To measure temperature dependent complex permittivity of dielectric materials, a rectangular cavity resonator with a heating system has been developed. In the experiment, microwave power with the frequency of 2.45 GHz is applied to heat the dielectric material. In order to reduce the error of the complex permittivity of dielectric material obtained from the perturbation method, an electromagnetic (EM) field simulator is applied which uses the Transmission Line Modeling (TLM) method. The uniformity of the temperature is also discussed by the use of heat transfer equation which applies the results of TLM simulation. It is found from the results that the accurate temperature dependence of complex permittivity of the material can be obtained by the method presented here.

We consider the routing for a multicast in a WDM all-optical network. We prove a min-max theorem on the number of wavelengths necessary for routing a multicast. Based on the min-max theorem, we propose an efficient on-line algorithm for routing a multicast.