Doron Nussbaum

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Traditional pattern recognition (PR) systems work with the model that the object to be recognized is characterized by a set of features, which are treated as the inputs. In this paper, we propose a new model for PR, namely one that involves chaotic neural networks (CNNs). To achieve this, we enhance the basic model proposed by Adachi (Neural Netw 10:83–98,(More)
We consider the well known geometric problem of determining shortest paths between pairs of points on a polyhedral surface P , where P consists of triangular faces with positive weights assigned to them. The cost of a path in P is defined to be the weighted sum of Euclidean lengths of the sub-paths within each face of P . We present query algorithms that(More)
The usual goal of modeling natural and artificial perception involves determining how a system can extract the object that it perceives from an image that is noisy. The "inverse" of this problem is one of modeling how even a clear image can be perceived to be blurred in certain contexts. To our knowledge, there is no solution to this in the literature other(More)
In application areas such as GIS, the Euclidean metric is often less meaningfully applied to determine a shortest path than metrics which capture, through weights, the varying nature of the terrain (e.g., water, rock, forest). Considering weighted metrics however increases the run-time of algorithms considerably suggesting the use of a parallel approach. In(More)
The longest increasing circular subsequence (LICS) of a list is considered. A Monte-Carlo algorithm to compute it is given which has worst case execution time O(n logn) and storage requirement O(n). It is proved that the expected length μ(n) of the LICS satisfies limn→∞ μ(n) 2 √ n = 1. Numerical experiments with the algorithm suggest that |μ(n) − 2 √ n| =(More)
We consider the classical geometric problem of determining shortest paths between pairs of points lying on a weighted polyhedral surface P consisting of n triangular faces. We present query algorithms that compute approximate distances and/or approximate (weighted) shortest paths. Our algorithm takes as input an approximation parameter ε ∈ (0, 1) and a(More)
In this paper we discuss the problem of determining a meeting point of a set of scattered robots R = {r1, r2, . . . , rs} in a weighted terrain P which has n > s triangular faces. Our algorithmic approach is to produce a discretization of P by producing a graph G = {V , E} which lies on the surface of P . For a chosen vertex p ∈ V , we define ‖Π(ri, p)‖ as(More)
This paper presents a computer-aided approach to enhancing suspicious lesions in digital mammograms. The developed algorithm improves on a well-known preprocessor filter named contrast-limited adaptive histogram equalization (CLAHE) to remove noise and intensity inhomogeneities. The proposed preprocessing filter, called fuzzy contrast-limited adaptive(More)
The Hodgkin-Huxley (HH) neuron is a nonlinear system with two stable states: A fixed point and a limit cycle. Both of them co-exist. The behavior of this neuron can be switched between these two equilibria, namely spiking and resting respectively, by using a perturbation method. The change from spiking to resting is named Spike Annihilation, and the(More)