2771138
Localization with dynamic motion models - determining motion model parameters dynamically in monte carlo localization
An electrical overload circuit breaker utilizes as the current-responsive tripping mechanism a solenoid, the coil of which is constituted by a helical spring of shape memory effect material and which mechanically acts on the armature. There is a non-SME spring which also acts on the armature but in a direction opposing the SME spring. The current is passed through the SME spring and, when it becomes excessive, the armature is urged both mechanically and electromagnetically in a tripping direction.
7940350
Experimental results towards content-based sub-image retrieval
We are interested in the problem of sub-image retrieval (CBSIR), i.e., given a query image one must find the best candidate images that contain that query image. We use two kinds of image feature vectors: global color histograms and autocorrelograms and experimented with several distance measures for both feature vectors in our experimental system. After extensive experimentation we found that using autocorrelograms with the so-called S/sub 1/ distance measure yielded excellent results for sub-image retrieval with an acceptable processing overhead.
10441616
Automatic Gait Optimization with Gaussian Process Regression
Gait optimization is a basic yet challenging problem for both quadrupedal and bipedal robots. Although techniques for automating the process exist, most involve local function optimization procedures that suffer from three key drawbacks. Local optimization techniques are naturally plagued by local optima, make no use of the expensive gait evaluations once a local step is taken, and do not explicitly model noise in gait evaluation. These drawbacks increase the need for a large number of gait evaluations, making optimization slow, data inefficient, and manually intensive. We present a Bayesian approach based on Gaussian process regression that addresses all three drawbacks. It uses a global search strategy based on a posterior model inferred from all of the individual noisy evaluations. We demonstrate the technique on a quadruped robot, using it to optimize two different criteria: speed and smoothness. We show in both cases our technique requires dramatically fewer gait evaluations than state-of-the-art local gradient approaches.
41375498
On line graphs which are weakly maximal clique irreducible
30326495
Performance-driven channel pin assignment algorithms
In this paper we consider two channel pin assignment problems which take circuit performance into account. The first one is the module implementation selection problem. We are given a net span bound for each critical net and each module has several possible placements of its pins. Our objective is to minimize channel density while satisfying net span constraints. We proved that this problem is NP-complete. For the case when each module has at most 2 pin placements, the problem can be transformed to the 2-SAT problem and hence is polynomial time solvable. We present a heuristic based on this algorithm to solve the general case. The second problem we consider is the module shifting problem. We are given a set of modules whose relative ordering is fixed on each side of the channel but their exact positions are not fixed. We present a polynomial time algorithm to test the feasibility of satisfying the net span constraints by shifting the modules. The algorithm is based on formulating the problem as a special integer linear programming problem which is solvable in polynomial time. We also extend our algorithms to handle multiple channels. >
18451647
Optimal circuit clustering for delay minimization under a more general delay model
This paper considers the area-constrained clustering of combinational circuits for delay minimization under a more general delay model, which practically takes variable interconnect delay into account. Our delay model is particularly applicable when allowing the back-annotation of actual delay information to drive the clustering process. We present a vertex grouping technique and integrate it with the algorithm (Rajaraman and Wong, 1995) such that our algorithm can be proved to solve the problem optimally in polynomial time.
14267974
Sample Rate Conversion Technology in Software Defined Radio
In this paper, a reconfigurable integer factor sample rate converter is proposed for software defined radio (SDR) receivers. A general principle for digital filter design in sample rate conversion (SRC) in SDR receivers can be summarized as that implementation efficiency is emphasized in the front stages, while high performance must be emphasized in the back stages. Based on this principle, a cascaded integrate comb (CIC) filter with factor-16 down sampler is used to realize large-factor and multiplier-free decimation in the front stage, while a multistage decimator is implemented together with the CIC filter to provide finer integral down sample rate. The multistage decimator is consisted of three stages, with each stage serving as a factor-2 down sampler. The Nyquist filters are used as anti-aliasing filter in the first two stages, and the linear phase equiripple filter is used in the last stage. In the end, the results of the sample rate conversion in SDR receiver are provided in this paper
6671884
Asymptotic Stationarity of Discrete-time Stochastic Neural Networks
Abstract This paper deals with a class of synchronous discrete-time stochastic neural network models. Dynamic stabilities (or asymptotic stationarities) are analysed for two sub-classes of the models, i.e., a class of stochasticized models from Little, and a class of Hopfield-type stochastic models. Copyright © 1996 Elsevier Science Ltd.