Providing various assistances for design modifications on HDL source codes is important for design reuse and quick design cycle in VLSI CAD. Program slicing is a software-engineering technique for analyzing, abstracting, and transforming programs. We show algorithms for extracting/removing behaviors of specified signals in VHDL descriptions. We also describe a VHDL slicing system and show experimental results of efficiently extracting components from VHDL descriptions.

A zerotree image-coding scheme is introduced that effectively exploits the inter-scale self-similarities found in the octave decomposition by a wavelet transform. A zerotree is useful for efficiently coding wavelet coefficients; its efficiency was proved by Shapiro's EZW. In the EZW coder, wavelet coefficients are symbolized, then entropy-coded for further compression. In this paper, we analyze the symbols produced by the EZW coder and discuss the entropy for a symbol. We modify the procedure used for symbol-stream generation to produce lower entropy. First, we modify the fixed relation between a parent and children used in the EZW coder to raise the probability that a significant parent has significant children. The modified relation is flexibly modified again based on the observation that a significant coefficient is more likely to have significant coefficients in its neighborhood. The three relations are compared in terms of the number of symbols they produce.

In many embedded systems, a significant amount of power is consumed for off-chip driving because off-chip capacitances are much larger than on-chip capacitances. This paper proposes instruction scheduling techniques to reduce power consumed for off-chip driving. The techniques minimize the switching activity of a data bus between an on-chip cache and a main memory when instruction cache misses occur. The scheduling problem is formulated and two scheduling algorithms are presented. Experimental results demonstrate the effectiveness and the efficiency of the proposed algorithms.

The datapath width of a core processor has a strong effect on cost, power consumption, and performance of an embedded system integrated with memories into a single-chip. However, it is difficult for designers to appropriately determine the datapath width for each application because of the limited reusability of software and the lack of compilation techniques. The purpose of this paper is to clarify supports required from software for the optimal datapath width determination. As a solution, an embedded programming language, called Valen-C, and a retargetable Valen-C compiler are proposed. In this paper, the syntax and semantics of Valen-C along with the mechanism of the Valen-C retargetable compiler and how to preserve the accuracy of computation of programs in relation to various datapath widths are also described. Experiments with practical applications show that the total cost of the system including a core processor, ROM, and RAM is drastically reduced with little performance loss by reducing the datapath width.

This paper proposes a novel signal transmission scheme for helicopter satellite communications. The proposed scheme is based on time diversity, and combined with a novel algorithm to suppress an influence of carrier phase slip. In the proposed scheme, carrier phase slip is detected in cross correlation processing of the received signal, and is effectively suppressed. The proposed scheme thus makes it possible to employ coherent phase shift keying modulation to achieve bit error rate performance superior to that of differential phase shift keying modulation even in the low carrier-to-noise power ratio environment.

Simple disjunctive decomposition is a special case of logic function decompositions, where variables are divided into two disjoint sets and there is only one newly introduced variable. It offers an optimal structure for a single-output function. This paper presents two techniques that enable us to apply simple disjunctive decompositions with little overhead. Firstly, we propose a method to find symple disjunctive decomposition forms efficiently by limiting decomposition types to be found to two: a decomposition where the bound set is a set of symmetric variables and a decomposition where the output function is a 2-input function. Secondly, we propose an algorithm that constructs a new logic representation for a simple disjunctive decomposition just by assigning constant values to variables in the original representation. The algorithm enables us to apply the decomposition with keeping good structures of the original representation. We performed experiments for decomposing functions and confirmed the efficiency of our method. We also performed experiments for restructuring fanout free cones of multi-level logic circuits, and obtained better results than when not restructuring them.

A novel image improving algorithm for compressed image sequence by merging a reference image is presented. A high quality still image of the same scene is used as a reference image. The degraded images are improved by merging reference image with them. Merging amount is controlled by the resemblance between the reference image and compressed image after applying motion compensation. Experiments conducted on sequences of JPEG images are given. This technique does not need a prior knowledge of compression technique so it can be applied to other techniques as well.

A Multi-Agent Learning Language (MALL) is defined as being necessary for agents in environments where they encounter crucial situations in which they have to learn about the environment, other parties moves and strategies, and then construct an optimal plan. The language is based on two major factors, the level of certainty in fully monitoring (surveying) the agents and the environment, and optimal plan construction, in an autonomous way. Most of the work related to software agents is based on the assumption that other agents are trustworthy. In the growing Internet environment this may not be true. The proposed new learning language allows agents to learn about the environment and the strategies of their opponents while devising their own plans. The language is being tested in our project of software agents for Electronic Commerce that operates in various security zones. The language is flexible and adaptable to a variety of agents applications.

This paper presents a new efficient method for finding an "optimal" bi-decomposition form of a logic function. A bi-decomposition form of a logic function is the form: f(X) = α(g1(X1), g2(X2)). We call a bi-decomposition form optimal when the total number of variables in X1 and X2 is the smallest among all bi-decomposition forms of f. This meaning of optimal is adequate especially for the synthesis of LUT (Look-Up Table) networks where the number of function inputs is important for the implementation. In our method, we consider only two bi-decomposition forms; (g1 g2) and (g1 g2). We can easily find all the other types of bi-decomposition forms from the above two decomposition forms. Our method efficiently finds one of the existing optimal bi-decomposition forms based on a branch-and-bound algorithm. Moreover, our method can also decompose incompletely specified functions. Experimental results show that we can construct better networks by using optimal bi-decompositions than by using conventional decompositions.

In this paper, we analyze the inverse scattering problem by a new deterministic method called "Source and Radiation Field Solution," which has the merit that both the source and the radiation field can be treated at the same time, the effect of which has already shown in ordinary scattering problems.

A unified source coding method is highly desired for many systems that deal with images diversifying from 1 bit/pel bi-level documents to SHD (Super High Definition) images of 12 bit/pel for each color component, and progressive coding that allows images to be reconstructed with increasing pixel accuracy or spatial resolution is essential for many applications including World Wide Web, medical images archive, digital library, pre-press and quick look applications. In this paper, we propose a unified continuous-tone and bi-level image coding method with pyramidal and progressive transmission feature. Hierarchical structure is constructed by interlacing subsampling, and each hierarchy is encoded by DPCM combined with reduced Markov model. Simulation results show that the proposed method is a little inferior than JBIG for bi-level image coding but can achieve better lossless compression ratio for gray-level image coding than CREW, in which wavelet transform is exploited to construct hierarchical structure.

This paper presents a new binding algorithm for a retargetable compiler which can deal with diverse architectures of application specific embedded processors. The architectural diversity includes a "non-orthogonal" datapath configuration where all the registers are not equally accessible by all the functional units. Under this assumption, binding becomes a hard task because inadvertent assignment of an operation to a functional unit may rule out possible assignment of other operations due to unreachability among datapath resources. We propose a new BDD-based algorithm to solve this problem. While most of the conventional methods are based on the covering of expression trees obtained by decomposing DFGs, our algorithm works directly on the DFGs so as to avoid infeasible bindings. In the experiments, a feasible binding which satisfies the reachability is found or the deficiency of datapath is detected within a few seconds.

This paper describes a new Artificial Neural Network (ANN), UNItary Decomposition ANN (UNIDANN), which can perform the unitary eigendecomposition of the synaptic weight matrix. It is shown both analytically and quantitatively that if the synaptic weight matrix is Hermitian positive definite, the neural output, based on the proposed dynamic equation, will converge to the principal eigenvectors of the synaptic weight matrix. Compared with previous works, the UNIDANN possesses several advantageous features such as low computation time and no synchronization problem due to the underlying analog circuit structure, faster convergence speed, accurate final results, and numerical stability. Some simulations with a particular emphasis on the applications to high resolution bearing estimation problems are also furnished to justify the proposed ANN.

The maximum order complexity (MOC) of a sequence is a very natural generalization of the well-known linear complexity (LC) by allowing nonlinear feedback functions for the feedback shift register which generates a given sequence. It is expected that MOC is effective to reduce such an instability of LC as an extreme increase caused by the minimum changes of a periodic sequence, i. e. , one-symbol substitution, one-symbol insertion or one-symbol deletion per each period. In this paper we will give the bounds (lower and upper bounds) of MOC for the minimum changes of an m-sequence over GF(q) with period qn-1, which shows that MOC is much more natural than LC as a measure for the randomness of sequences in this case.

In the task of forming high-level object-centered models from low-level image-based features, parts serve as an intermediate representation. A representation of parts for object recognition should be rich, stable, and invariant to changes in the viewing conditions. In addition, it should be capable of describing partially occluded shapes. This paper describes a method for decomposing shapes into parts. The method is based on pairs of negative curvature minima which have a good continuation at their boundary tangents. A measure of good continuation is proposed by using the coefficients of cocircularity, smoothness, and proximity. This method could recover parts in a direct computation, therefore efficient in calculation than the former. Currently, we assume that the shape is a closed planar curve.

This paper presents a performance comparison between the single-stream and the multi-stream approaches to lip synchronization of live media (voice and video). The former transmits a single transport stream of interleaved voice and video, while the latter treats the two media as separate transport streams. Each approach has an option not to exert the synchronization control at the destination, which leads to four basic schemes. On an interconnected ATM-wireless LAN, we implemented the four basic schemes with RTP/RTCP on top of UDP and two variants which exercise dynamic resolution control of JPEG video. Making the performance measurement of the six schemes, we compare them to identify and evaluate advantages and disadvantages of each approach. We then show that the performance difference between the two approaches is small and that the dynamic resolution control improves the synchronization quality.

This letter reports on the condition for applying a feedback connection to a deterministic finite automata. First we define the partial delayed dependence condition for the feedback connection, and then consider problems related to the completeness problem of automata.

This paper formulates problems of fitting two corresponding sets of points by translation, rotation and scaling, and proposes efficient algorithms for the fitting. The algorithms are based on the theory of lower envelopes, or Davenport-Schinzel sequences, and linearization techniques in computational geometry, and are related to dynamic furthest Voronoi diagrams.

Cursor RAMs have been composed of two memory planes. A cursor pattern is stored in these planes with 2-bit data depth. While the pixel port requires data from both planes at the same time, the MPU port accesses either one of the planes at a time. Since the address space is defined differently between the ports, conventional cursor RAMs could not have dealt with these different access ways at real time. This paper proposes a dual port cursor RAM with a dynamic data alignment architecture. The architecture processes the different access ways at real time, and reduces a large amount of control circuitry. Conventional cursor RAMs have been organized with a single port memory because dual port memory cells have been large. We have applied the port swap architecture which has reduced the cell size. The control block is further simplified because the controller no longer emulate a dual port memory. The cursor RAM with these architectures is fabricated with a double metal 0. 5 µm CMOS process technology. The active area is 1. 51. 6 mm2 including a couple of shift registers and a control block. It operates up to 263 MHz at the supply voltage of 3. 3 V.

Reducing communication overhead is a key goal of program optimization for current scalable multiprocessors. A well-known approach to achieving this is to map tasks (indivisible units of computation) to processors so that communication and computation overlap as much as possible. In an earlier work, we developed a look-ahead scheduling heuristic for efficiently reducing communication overhead with the aim of decreasing the completion time of a given parallel program. In this paper, we report on an extension of the algorithm, which fills in the idle time slots created by interprocessor communication without increasing the algorithm's time complexity. The results of experiments emphasize the importance of optimally filling idle time slots in processors.