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Hierarchical clustering has been well-studied in the community of machine learning. Hierarchical clustering algorithms are deterministic, stable, and do not need a pre-determined number of clusters as input. However, they are not scalable for very large data due to their non-linear complexity. In this paper, a new approach is proposed to reduce the complexity of Hierarchical Clustering, improve the...
Nowadays, complex hybrid systems, whose behavior combines continuous and discrete event dynamics, are applied in many engineering applications, from electrical circuits to aircraft systems. However, diagnosis of hybrid system, which is composed of components involving multiple modes, demands unfordable computation due to high complexity and its exponential behaviors caused by combinational explosion...
We present a case study of feature location in industry. We study two off-the-shelf feature location algorithms for use as input to a software cost estimator. The feature location algorithms that we studied map program requirements to one or more function points. The cost estimator product, which is the industrial context in which we study feature location, transforms the list of function points into...
A MUSIC-ML (MML) processing algorithm for 3-dimensional localization of underwater acoustic sources using a 2-dimensional acoustic vector (AVS) array was proposed recently. The MML processor performs source localization with high accuracy and resolution. But the hardware and computational complexity of the MML processor is very high. In this paper we propose the use of compressive sampling of the...
Software Projects are developed with the prior requirements and should be capable to complete on time under a fixed budget but it gets late to delivered, gets over-budget and even not able to meet user expectations. In agile approach, the estimation of software depends on expert opinion or on any historical data which is used as the input to previous methods like planning poker. The accuracy in estimation...
Software metrics can be classified in to two categories of code metrics and architectural metrics [1,2]. Code metrics basically consider analysis of data structures and algorithms for determining the complexity of the program [3,4,5]. Whereas architectural metrics consider the mechanism how system is processing data within its components and any existing dependencies between the processed data for...
Noise energy estimation is widely used as a pre-process in speech enhancement and speech recognition systems. While many signal processing algorithms have been proposed to estimate the additive noise energy, they are generally based on some statistical hypothesis and have high computation complexity, which is crucial in mobile devices. When the hypothesis does not hold, the estimation performance...
Nowadays, instructors have many different methodologies to assess students. Formative and summative models are mainly applied to multiple combinations independently of the learning environment (on-site, online or blended). When we move to an adaptive learning, students are assessed depending on the selected learning path and the scheduled assessment activities. The adaption tends to be in the learning...
Relay node placement in wireless sensor networks for constrained environment is a critical task due to various unavoidable constraints. One of the most important constraints is unpredictable obstacles. Handling obstacles during relay node placement is complicated because of complexity involved to estimate the shape and size of obstacles. This paper presents an Obstacle-resistant relay node placement...
Currently, because of the exponential growth of vulnerabilities, one of the most essential requirements for IT managers is to improve network security by eliminating vulnerabilities that are most hazardous. Achieving this goal requires ranking vulnerabilities based on their peril to the network. Today, this target has become possible by introducing open standards such as Common Vulnerability Scoring...
In this paper, we study the performances of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) and universal filtered orthogonal frequency division multiplexing (UF-OFDM) in the presence of phase noises. A phase noise mitigation scheme was proposed for CP-OFDM in a previous work. In this work, we extend the scheme to UF-OFDM. Phase noise estimation parameters are studied extensively...
Parametric motion models are commonly used in image sequence analysis for different tasks. A robust estimation framework is usually required to reliably compute the motion model. The choice of the right model is also important. However, dealing simultaneously with both issues remains an open question. We propose a robust motion model selection method with two variants, which relies on the Fisher test...
Video retrieval and video copy detection are well studied problems. The goal is to find the matching video in a database from a given query video. Typically, these query videos are short and aligning the query video is of secondary importance. Short sequences can be aligned using dynamic time warping. But, since time and memory usage increases quadratically with the length of the sequences, such process...
We investigate power dissipation/performance trade-off in a 28nm ASIC implementation of a parallel dynamic equalizer. Over 50% dissipation improvement is possible by sample pruning during filter updates, with only minor tracking-performance reduction.
We propose an enhancement to the fast blind CD estimation method based on auto-correlation of signal power. The use of Hartley and Cosine transform allow 30% and 70% complexity reductions, within a maximum loss of 2% in accuracy.
This paper describes a novel design method for direct digital frequency synthesizers with very high accuracy. To this end, we leverage the well-known piecewise, multiplier-less function approximation method by two separate enhancements: A parallel function estimation scheme is applied which increases the approximation accuracy and reduces the segmentation effort. To achieve further performance improvement,...
Improving the execution time and the numerical complexity of the well-known kurtosis-based maximization method, the RobustICA, is investigated in this paper. A Newton-based scheme is proposed and compared to the conventional RobustICA method. A new implementation using the nonlinear Conjugate Gradient one is investigated also. Regarding the Newton approach, an exact computation of the Hessian of the...
The study evaluates the k-nearest-neighbor (KNN) strategy for the assessment of complexity of the cardiac neural control from spontaneous fluctuations of heart period (HP). Two different procedures were assessed: i) the KNN estimation of the conditional entropy (CE) proposed by Porta et al; ii) the KNN estimation of mutual information proposed by Kozachenko-Leonenko, refined by Kraskov-Stögbauer-Grassberger...
Estimation is very important and integral part of software development life cycle. Without estimation of effort, duration and cost, software cannot be developed. It is important to do accurate estimation as much as possible. Today in Information technology Industry Estimation in agile software development is mostly based on heuristic approaches like expert judgment and planning poker. In absence of...
Physical systems switching between various working regimes are often encountered in practical applications. However, transition probabilities, according to which a system switches from the current regime to another one, are commonly designed as a priori known parameters, and their misspecification can degrade the performance of the algorithms filtering (or estimating) latent variables of the system...
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