Search results for "Computational complexity theory"
showing 10 items of 111 documents
Simplified spiking neural network architecture and STDP learning algorithm applied to image classification
2015
Spiking neural networks (SNN) have gained popularity in embedded applications such as robotics and computer vision. The main advantages of SNN are the temporal plasticity, ease of use in neural interface circuits and reduced computation complexity. SNN have been successfully used for image classification. They provide a model for the mammalian visual cortex, image segmentation and pattern recognition. Different spiking neuron mathematical models exist, but their computational complexity makes them ill-suited for hardware implementation. In this paper, a novel, simplified and computationally efficient model of spike response model (SRM) neuron with spike-time dependent plasticity (STDP) lear…
Wavelet Frames Generated by Spline Based p-Filter Banks
2014
This chapter presents a design scheme to generate tight and so-called semi-tight frames in the space of discrete-time periodic signals. The frames originate from oversampled perfect reconstruction periodic filter banks. The filter banks are derived from discrete-time and discrete periodic splines. Each filter bank comprises one linear phase low-pass filter (in most cases interpolating) and one high-pass filter, whose magnitude response mirrors that of a low-pass filter. In addition, these filter banks comprise a number of band-pass filters. In this chapter, frames generated by four-channel filter banks are briefly outlined (see Chap. 17 in [2] for details) and tight frames generated by six-…
Steady-state and tracking analysis of a robust adaptive filter with low computational cost
2007
This paper analyses a new adaptive algorithm that is robust to impulse noise and has a low computational load [E. Soria, J.D. Martin, A.J. Serrano, J. Calpe, and J. Chambers, A new robust adaptive algorithm with low computacional cost, Electron. Lett. 42 (1) (2006) 60-62]. The algorithm is based on two premises: the use of the cost function often used in independent component analysis and a fuzzy modelling of the hyperbolic tangent function. The steady-state error and tracking capability of the algorithm are analysed using conservation methods [A. Sayed, Fundamentals of Adaptive Filtering, Wiley, New York, 2003], thus verifying the correspondence between theory and experimental results.
Three-dimensional phase unwrapping using the Hungarian algorithm.
2009
We propose a three-dimensional phase unwrapping technique that uses the Hungarian algorithm to join together all the partial residual loops that may occur in a wrapped phase volume. Experimental results have shown that the proposed algorithm is more robust and reliable than other well-known three-dimensional phase unwrapping algorithms. Additionally, the proposed algorithm is fast in terms of computational complexity, which makes it suitable for practical applications.
Evaluation of GPU-based Seed Generation for Computational Genomics Using Burrows-Wheeler Transform
2012
Unprecedented production of short reads from the new high-throughput sequencers has posed challenges to align short reads to reference genomes with high sensitivity and high speed. Many CPU-based short read aligners have been developed to address this challenge. Among them, one popular approach is the seed-and-extend heuristic. For this heuristic, the first and foremost step is to generate seeds between the input reads and the reference genome, where hash tables are the most frequently used data structure. However, hash tables are memory-consuming, making it not well-suited to memory-stringent many-core architectures, like GPUs, even though they usually have a nearly constant query time com…
Two-way quantum and classical machines with small memory for online minimization problems
2019
We consider online algorithms. Typically the model is investigated with respect to competitive ratio. In this paper, we explore algorithms with small memory. We investigate two-way automata as a model for online algorithms with restricted memory. We focus on quantum and classical online algorithms. We show that there are problems that can be better solved by two-way automata with quantum and classical states than classical two-way automata in the case of sublogarithmic memory (sublinear size).
Work Partitioning on Parallel and Distributed Agent-Based Simulation
2017
Work partitioning is a key challenge with ap- plications in many scientific and technological fields. The problem is very well studied with a rich literature on both distributed and parallel computing architectures. In this paper we deal with the work partitioning problem for parallel and distributed agent-based simulations which aims at (i) balancing the overall load distribution, (ii) minimizing, at the same time, the communication overhead due to agents' inter-dependencies. We introduce a classification taxonomy of work partitioning strategies and present a space-based work partitioning ap- proach, based on a Quad-tree data structure, which enables to: identify a good space partitioning …
An improved quantum query algorithm for computing AND Boolean function
2010
We consider the quantum query model for computing Boolean functions. The definition of the function is known, but a black box contains the input X = (x 1 , x 2 , …, x n ). Black box can be accessed by querying x i values. The goal is to develop an algorithm, which would compute the function value for arbitrary input using as few queries to the black box as possible. We present two different quantum query algorithms for computing the basic Boolean function — logical AND of two bits. Both algorithms use only one query to determine the function value. Correct answer probability for the first algorithm is 80%, but for the second algorithm it is 90%. To compute this function with the same probab…
Extracting string motif bases for quorum higher than two
2012
Bases of generators of motifs consisting of strings in which some positions can be occupied by a don’t care provide a useful conceptual tool for their description and a way to reduce the time and space involved in the discovery process. In the last few years, a few algorithms have been proposed for the extraction of a basis, building in large part on combinatorial properties of strings and their autocorrelations. Currently, the most efficient techniques for binary alphabets and quorum q = 2 require time quadratic in the length of the host string. The present paper explores properties of motif bases for quorum q ≥ 2, both with binary and general alphabets, by also showing that important resu…
Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks
2021
The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the po…