This paper proposes a simple and efficient method to numerically obtain the mapping degree deg( f , 0, B) of a C1 map f : Rn → Rn at a regular value 0 relative to a bounded open subset B ⊂ Rn. For practical application, this method adopts Aberth’s algorithm which does not require computation of derivatives and determinants, and reduces the computational cost with two additional procedures, name...

We use dense variable-ordering to define HRD (Hybrid-Restriction Diagram), a new BDD-like datastructure for the representation and manipulation of state-spaces of linear hybrid automata. We present and discuss various manipulation algorithms for HRD, including the basic set-oriented operations, weakest precondition calculation, and normalization. We implemented the ideas and experimented to see...

SUMMARY This paper describes an optimal scheduling approach which nds the scheduling result of the minimum functional unit cost under the given timing constraint. In this method, a well-deened search space is constructed incremen-tally and traversed in a branch-and-bound manner. During the traversal, tighter lower bounds are estimated and utilized coupled with the upper bound on the optimal sol...

We \vill present research associated }vith the sound modeling soft$~rare called Lemur. In Lemur, Jve have developed a ne}v extension LOthe sinusoidal modeling technique of McAulay and Qua~ieri to accommodate sounds having significant non-sinusoidal energy. Lemur models sounds as a collection of par[ials having amplitude, frequency, and band!vidth envelopes. Band!vidth envelopes allotv Lemur [o ...

We present a modelling method and graphical user interface for the creation of natural branching structures such as plants. Structural and geometric information is encapsulated in objects that are combined to form a description of the model. The model is represented graphically as an structure graph and can be edited interactively. Global and partial constraint techniques are integrated on the ...

Forward pruning, or selectively searching a subset of moves, is now commonly used in game-playing programs to reduce the number of nodes searched with manageable risk. Forward pruning techniques should consider how pruning errors in a game-tree search propagate to the root to minimize the risk of making errors. In this paper, we explore forward pruning using theoretical analyses and Monte Carlo...

Decision tree technology has proven to be a valuable way of capturing human decision making within a computer. It has long been a popular artificial intelligence(AI) technique. During the 1980s, it was one of the primary ways for creating an AI system. During the early part of the 1990s, it somewhat fell out of favor, as did the entire AI field in general. However, during the later 1990s, with ...

A large-scale pruning study was established in the winter of 1999 to2000 at seven different sites on Green Diamond Resource Company forestlands in Humboldt County. The objective of this study was to determine the effects of pruning on increment, epicormic sprouting, stem taper, heartwood formation, and bear damage on these young trees. Pruning treatments varied pruning severity and were usually...

Most speech recognition systems search through large finite state machines to find the most likely path, or hypothesis. Efficient search in these large spaces requires pruning of some hypotheses. Popular pruning techniques include probability pruning which keeps only hypotheses whose probability falls within a prescribed factor from the most likely one, and rank pruning which keeps only a presc...

The pruning phase is one of the necessary steps in decision tree induction. Existing pruning algorithms tend to have some or all of the following difficulties: 1) lack of theoretical support; 2) high computational complexity; 3) dependence on validation; 4) complicated implementation. The 2-norm pruning algorithm proposed here addresses all of the above difficulties. This paper demonstrates the...