This paper proposes a fast timing recovery method with a decision feedback equalizer for baudrate sampling. The proposed method features two special techniques. The first one is for coarse estimation of the sampling phase. Internal signals of the oversampled analog-to-digital converter at different phases are directly taken out for parallel evaluation. The second technique provides fine tuning with a phase-modification stepsize which is adaptively controlled by the residual intersymbol interference. Simulation results by a full-duplex digital transmission system with a multilevel line code show superiority of the proposed method. The coarse timing estimation and the fine tuning reduce 75% and 40% of the time required by the conventional method,respectively. The overall saving in timing recovery is almost 60% over the conventional method. The proposed method could easily be extended to other applications with a decision feedback equalizer.

The up and coming multimedia services are based on real-time high-speed networks. For efficient operation of such services, real-time and precise network management is essential. In this paper, we show that presently available MIB designs are severely inadequate to support real-time network management. We point out and analyze the management constraints and bottlenecks. The concept of quality of management of management information is introduced and its importance in practical network management is discussed. We have proposed a new MIB architecture that will raise the quality of management information to meet the requirements of managing high-speed networks and multimedia services. Experimental results from a prototype implementation of the new MIB architecture are presented.

This paper introduces a new method to recover 3-D road plane from its 2-D monocular perspective image. The research is aimed at the reconstruction of depth information from the 2-D visual input in road following and navigation. Planar road model is considered and the road-centered coordinate system which forms slope and turn angles with camera-centered coordinate system is used to describe boundary points on road plane. We develop approaches to find matching points of boundaries of road and to obtain angular parameters thereafter. A way of finding depth of matching points from the perspective images and angular parameters together is proposed. Therefore the 3-D road reconstruction can be replicated without introducing any parameters of inverse perspective.

For reducing requirement of large memory and minimizing computation complexity in a large-vocabulary continuous speech recognition system, speech segmentation plays an important role in speech recognition systems. In this paper, we formulate the speech segmentation as a two-phase problem. Phase 1 (frame labeling) involves labeling frames of speech data. Frames are classified into three types: (1) silence, (2) consonant and (3) vowel according to two segmentation features. In phase 2 (syllabic unit segmentation) we apply the concept of transition states to segment continuous speech data into syllabic units based on the labeled frames. The novel class of hyperrectangular composite neural networks (HRCNNs) is used to cluster frames. The HRCNNs integrate the rule-based approach and neural network paradigms, therefore, this special hybrid system may neutralize the disadvantages of each alternative. The parameters of the trained HRCNNs are utilized to extract both crisp and fuzzy classification rules. In our experiments, a database containing continuous reading-rate Mandarin speech recorded from newscast was utilized to illustrate the performance of the proposed speaker independent speech segmentation system. The effectiveness of the proposed segmentation system is confirmed by the experimental results.

This paper considers the estimation of speech parameters and their enhancement using an approach based on the estimation-maximization (EM) algorithm, when only noisy speech data is available. The distribution of the excitation source for the speech signal is assumed as a mixture of two Gaussian probability distribution functions with differing variances. This mixture assumption is experimentally valid for removing the residual excitation signal. The assumption also is found to be effective in enhancing noise-corrupted speech. We adaptively estimate the speech parameters and analyze the characteristics of its excitation source in a sequential manner. In the maximum likelihood estimation scheme we utilize the EM algorithm, and employ a detection and an estimation step for the parameters. For speech enhancement we use Kalman filtering for the parameters obtained from the above estimation procedure. The estimation and maximization procedures are closely coupled. Simulation results using synthetic and real speech vindicate the improved performance of our algorithm in noisy situations, with an increase of about 3 dB in terms of output SNR compared to conventional Gaussian assumption. The proposed algorithm also may be noteworthy in that it needs no voiced/unvoiced decision logic, due to the use of the residual approach.

This paper presents a method for mechanically transforming a parallel algorithm on an original network so that the algorithm can work on a target network. It is assumed that the networks are of cube-type such as the shuffle-exchange network, omega network, and hypercube. Were those networks isomorphic to each other, the algorithm transformation is an easy task. The proposed transformation method is based on a novel graphembedding scheme <φ: δ, κ, π, ψ>. In addition to the dilating operation δ of the usual embedding scheme <φ: δ>, the novel scheme uses three primitive graph-transformation operations; κ (= δ-1) for contracting a path into a node, π for pipelining a graph, and ψ (= π-1) for folding a pipelined graph. By applying the primitive operations, the cube-type networks can be transformed so as to be isomorphic to each other. Relationships between the networks are represented by the composition of applied operations. With the isomorphic mapping φ, an algorithm in a node of the original network can be simulated in the corresponding node(s) of the target network. Thus the algorithm transformation is reduced to routine work.

The effect of silicone vapour concentration on the contact failure was examined by using micro relays and motor brush-slip ring(commutator) contacts, [(CH3) 2SiO]4: D4 was used as a vapour source of silicone contamination. Because the influence of the vapour of the silicone on the contact surface can not be avoided at all times due to its gradual evaporation in the atmosphere. The contact failure caused by the silicone vapour was confirmed as formation of SiO2 on the contact surfaceby analysis of EPMA and XPS. A minimum limiting concentration level which does not affect contact reliability was found. This limiting level was 10 ppm(O.13mg/l). Validity of the limiting level was confirmed by the relationships among concentration, temperature, SiO2 film thickness and contact resistance. Furthermore, the effect of the degree of silicone polymerization on the limiting concentration was derived by an empirical formula. This silicone is found to have polymerization degree larger than D7: n=7. These results were confirmed by the contact failure data due to the silicone contamination.

Three techniques are proposed for reducing the time required for protocol processing: protocol data unit management using page management, assembly and disassembly of data packet header and contents in hardware, and rescheduling of protocol processing. These techniques were shown to be feasible by applying them to the TCP/IP over a fiber-distributed data interface network. The maximum communication throughput was 91.6 Mbps; the total throughput for 64 sessions was 89.6 Mbps, only 2% less than the maximum. These techniques will enable the development of more effcient video-on -demand systems.

String grammars (languages) have been extensively studied from 60's. On the other hand, the transformational grammar, proposed by N. Chomsky, contains the transformation from the set of derivation trees of context-free language to the surface set. And the grammar regarded a tree as an input sentence to some transducer. After that from latter half of 60's, the studies of acceptors, transducers, and so on, whose input is a tree, have been studied extensively. And recently some pushdown tree automata were introduced, and their fundamental properties and some other various properties were investigated [11]-[17]. Furthermore, a top-down pushdown tree transducer (t-PDTT for short), which is an extension of a top-down pushdown automaton (t-PDTA for short), was introduced and its fundamental properties were investigated [19]. In this paper, we define the various subclasses of context-free tree grammar (CFTG for short) by the combination of variables contained in the rules. Furthermore, we consider a monadic case of CFTG which is a special case of CFTG. Based on these definitions, we classify the subclasses of CFTG, and we investigate some inclusion properties of subclasses of CFTL (where CFTL indicates the class of context-free tree languages).

This paper proposes Channel Reservation for Ahead Cells (CRAC)" scheme for street micro-cellular systems. The scheme enables mobiles to reserve the same channel over several cells at once. This paper analyzes both CRAC and FCA (Fixed Channel Assignment) in a ring-shaped service area where high speed mobiles and low speed mobiles move. In the analysis, the priority control which prioritizes hand-off calls and reservation calls over new calls over new calls is also taken into account. Obtained results include the blocking rate, the forced call termination rate, the average number of channel changings and the system utilization. From numerical results, CRAC is found to perform better than FCA with regard to the average number of channel changings and the forced call termination rate.

This paper describes a new and realisable speech enhancement structure which simulates the cocktail party effect with a modified iterative Wiener filter and a multi-layer perceptron neural network. The key idea is to use the neural network as a speaker recognition system to govern the iterative Wiener filter. The neural network is a modified perceptron with a hidden layer using feature date extracted from LPC cepstral analysis. The proposed technique has been successfully used for speech enhancement when the interference is competing speech or broad band noise.

This paper reports a 32k32 1-Mbit CMOS synchronous pipelined burst SRMA. A clock access time of 3.6 ns and a minimum cycle time of 9 ns(111 MHz operation) were obtained. An active current of 210 mA at 111 MHz and a standby current of 2 µA were successfully realized. These results can be obtained by a new activation control method in which the internal clock pulses control the decoders, the low resistive bit line and memory cell GND line and the optimization of write recovery timing and data sense timing.

A algorithm for designing a pattern classifier, which uses MDL criterion and a binary data structure, is proposed. The algorithm gives a partitioning of the range of the multi-dimensional attribute and gives an estimated probability model for this partitioning. The volume of bins in this partitioning is upper bounded by ο((log N/N)K/(K+2)) almost surely, where N is the length of training sequence and K is the dimension of the attribute. The convergence rates of the code length and the divergence of the estimated model are asymptotically upper bounded by ο((log N/N)2/(K+2)). The classification error is asymptotically upper bounded by ο((log N/N)1/(K+2)). Simulation results for 1-dimensional and 2-dimensional attribute cases show that the algorithm is practically efficient.

We propose a speech recognition method using fusion of auditory and visual information for accurate speech recognition. Since we use both auditory information and visual information, we can perform speech recognition more accurately in comparison with the case of either auditory information or visual information. After processing each information by HMM, they are fused by linear combination with weight coefficient. We performed experiments and confirmed the validity of the proposed method.

This paper discusses how to derive message sequence charts (MSCs) from a set of state transition descriptions. Recently, MSC notation has received much attention in the communications software field because it graphically shows system global behavior, So MSC handling techniques are being widely studied. These studies have recommended the design a system by a set of formal MSCs in the early stages of development and then to convert them into state transition descriptions. However, it is difficult to apply those results to existing communications software products. This is because these systems are designed based on state transition descriptions and there are no formal MSCs for them. In this paper, we propose a method of deriving MSCs based on optimized reachability analysis. This method generates MCSs that avoid state explosion. A case study using Q.931 protocol shows the feasibility of this method.

String grammars (languages) have been extensively studied from the 60's. On the other hand, the transformational grammar, proposed by N. Chomsky, contains the transformation from the set of derivation trees of a context-free language to the surface set. Here the grammar regarded a tree as an input sentence to some transducer. After that from the second half of 60's, the studies of acceptors, transducers, and so on, whose inputs are trees, have been done extensively. Recently pushdown tree automata were introduced, and their fundamental and some other various properties were investigated [12],[13],[22]-[26]. Furthermore a top-down pushdown tree transducer (t-PDTT for short), which is an extension of a top-down pushdown automaton (t-PDTA for short), was introduced and its fundamental properties were investigated [27]. In this paper we focus on t-PDTT, linear t-PDTT, t-FST (top-down finite state transducer), and t-PDTA. The main subjects discussed here are as follows: (1) the class of domain/surface tree languages of t-PDTT properly contains the class of tree languages accepted by t-PDTA, (2) the class of domain/surface tree languages of linear t-PDTT's coincides with the class of tree languages accepted by t-PDTA's, (3) the class of tree languages accepted by t-PDTA's properly contains the class of surface tree languages of t-FST's.

This paper describes methods in which natural language is used to describe video contents, knowledge of which is needed for intelligent video manipulation. The content encoded by natural language is extracted by a language analyzer in the form of subject-centered dependency structures which is a language-oriented structure, and is combined in an incremental way into a single structure called a multi-path index tree. Content descriptors and their inter-relations are extracted from the index tree in order to provide a high speed retrieval and flexibility. The content-based video index is represented in a two-dimensional structure where in the descriptors are mapped onto a component axis and temporal references (i.e., video segments aligned to the descriptors) are mapped onto a time axis. We implemented an experimental image retrieval systems to illustrate the proposed index structure 1) has superior retrieval capabilities compare to those used in conventional methods, 2) can be generated by an automated procedure, and 3) has a compact and flexible structure that is easily expandable, making an integration with vision processing possible.

In this paper we propose an effective ratebased virtual clock (ERVC) scheduling algorithm which is applied to the switching nodes in the connection-oriented high-speed networks. It is based on the effective rate which has a value between the average and peak transmission rates. The algorithm is simple but overcomes the defects of original virtual-clock algorithm. Performance results demonstrate the effectiveness of the ERVC algorithm in comparison with other methods.

In order to display complicated virtual spaces in real time, such as spaces consisting of a dynamic natural scenery, we earlier proposed a method for simplifying the shape data of 3-D trees whereby the amount of shape data is efficiently reduced. The method generates tree shapes based on a fractal model according to the required level of details (LOD). By using a texture-mapping technique, we experimentally showed that our method can display 3-D tree images with allowable image quality in real time. However, methods for controlling the LOD of 3-D tree shapes in virtual spaces have yet to be discussed. In this paper, quantitative evaluations were made on the effect of a data simplification method employing such visual properties as resolution difference between the central vision and peripheral vision. Results showed that it is possible to display a complicated scene containing many trees in real time by controlling the LOD of tree shapes in the virtual space considering such visual properties. Furthermore, so that reality can be added to the virtual space, we consider that it is important to display the natural sways of wind-blown trees and plants in real time. Therefore, we propose a method for generating sway data for simplified tree shape data based on a simple physical model, in which each branch is connected to several other branches by springs, and also a new texture-mapping technique for rendering simplified tree shapes, making it appear as if the shapes have a high LOD. Finally, we show some examples of images of trees generated in real time by using our method, in which many trees exist and sway due to wind.

We have fabricated a new analog memory for integrated artificial neural networks. Several attempts have been made to develop a linear characteristics of floating-gate analog memorys with feedback circuits. The learning chip has to have a large number of learning control circuit. In this paper, we propose a new analog memory SDAM with three cascaded TFTs. The new analog memory has a simple design, a small area occupancy, a fast switching speed and an accurate linearity. To improve accurate linearity, we propose a new chargetransfer process. The device has a tunnel junction (poly-Si/poly-Si oxide/poly-Si sandwich structure), a thin-film transistor, two capacitors, and a floating-gate MOSFET. The diffusion of the charges injected through the tunnel junction are controlled by a source follower operation of a thin film transistor (TFT). The proposed operation is possible that the amounts of transferred charges are constant independent of the charges in storage capacitor.