—In this paper, we introduce a new approach to computing a Morse decomposition of a vector field on a triangulated manifold surface. The basic idea is to convert the input vector...
The population vector is a linear decoder for an ensemble of neurons, whose response properties are nonlinear functions of the input vector. However, previous analyses of this deco...
M. Brandon Westover, Chris Eliasmith, Charles H. A...
Tree-Structured Vector Quantization (TSVQ) is a highly efficient technique for locating an appropriate codeword for each input vector. The algorithm does not guarantee that the sel...
The condition-based approach for consensus solvability (that we have introduced in a previous paper, ACM STOC'01) consists in identifying sets of input vectors for which it i...
Abstract. Consider a system composed of n sensors operating in synchronous rounds. In each round an input vector of sensor readings x is produced, where the i-th entry of x is a bi...
Florent Becker, Sergio Rajsbaum, Ivan Rapaport, Er...
The ability to store and retrieve information is critical in any type of neural network. In neural network, the memory particularly associative memory, can be defined as the one i...
We propose a hierarchical, unsupervised clustering algorithm (TreeGCS) based upon the Growing Cell Structure (GCS) neural network of Fritzke. Our algorithm improves an inconsisten...
Accurate power estimation is essential for low power digital CMOS circuit design. Power dissipation is input pattern dependent. To obtain an accurate power estimate, a large input...
Chi-Ying Tsui, Radu Marculescu, Diana Marculescu, ...
A vector algorithm is an algorithm that applies a bounded number of vector operations to an input vector, regardless of the length of the input. In this paper, we describe the link...
—1As technology scales, the aging effect caused by Negative Bias Temperature Instability (NBTI) has become a major reliability concern for circuit designers. On the other hand, r...
Yu Wang 0002, Xiaoming Chen, Wenping Wang, Yu Cao,...