Signal Processing Commons^™

An Empirical Comparison Of The Security And Performance Characteristics Of Topology Formation Algorithms For Bitcoin Networks, Muntadher Sallal, Ruairí De Fréin, Ali Malik, Benjamin Aziz

Articles

There is an increasing demand for digital crypto-currencies to be more secure and robust to meet the following business requirements: (1) low transaction fees and (2) the privacy of users. Nowadays, Bitcoin is gaining traction and wide adoption. Many well-known businesses have begun accepting bitcoins as a means of making financial payments. However, the susceptibility of Bitcoin networks to information propagation delay, increases the vulnerability to attack of the Bitcoin network, and decreases its throughput performance. This paper introduces and critically analyses new network clustering methods, named Locality Based Clustering (LBC), Ping Time Based Approach (PTBC), Super Node Based Clustering …

Offline And Online Density Estimation For Large High-Dimensional Data, Aref Majdara

Dissertations, Master's Theses and Master's Reports

Density estimation has wide applications in machine learning and data analysis techniques including clustering, classification, multimodality analysis, bump hunting and anomaly detection. In high-dimensional space, sparsity of data in local neighborhood makes many of parametric and nonparametric density estimation methods mostly inefficient.

This work presents development of computationally efficient algorithms for high-dimensional density estimation, based on Bayesian sequential partitioning (BSP). Copula transform is used to separate the estimation of marginal and joint densities, with the purpose of reducing the computational complexity and estimation error. Using this separation, a parallel implementation of the density estimation algorithm on a 4-core CPU is …

Basic Science To Clinical Research: Segmentation Of Ultrasound And Modelling In Clinical Informatics, Ali K. Hamou

Electronic Thesis and Dissertation Repository

The world of basic science is a world of minutia; it boils down to improving even a fraction of a percent over the baseline standard. It is a domain of peer reviewed fractions of seconds and the world of squeezing every last ounce of efficiency from a processor, a storage medium, or an algorithm. The field of health data is based on extracting knowledge from segments of data that may improve some clinical process or practice guideline to improve the time and quality of care. Clinical informatics and knowledge translation provide this information in order to reveal insights to …

Next Generation Of Product Search And Discovery, Kaiman Zeng

FIU Electronic Theses and Dissertations

Online shopping has become an important part of people’s daily life with the rapid development of e-commerce. In some domains such as books, electronics, and CD/DVDs, online shopping has surpassed or even replaced the traditional shopping method. Compared with traditional retailing, e-commerce is information intensive. One of the key factors to succeed in e-business is how to facilitate the consumers’ approaches to discover a product. Conventionally a product search engine based on a keyword search or category browser is provided to help users find the product information they need. The general goal of a product search system is to enable …

Portfolio Diversification Using Subspace Factorizations, Ruairí De Fréin, Konstantinos Drakakis, Scott Rickard

Conference papers

Successful investment management relies on allocating assets so as to beat the stock market. Asset classes are affected by different market dynamics or latent trends. These interactions are crucial to the successful allocation of monies. The seminal work on portfolio management by Markowitz prompts the adroit investment manager to consider the correlation between the assets in his portfolio and to vary his selection so as to optimize his riskreturn profile. The factor model, a popular model for the return generating process has been used for portfolio construction and assumes that there is a low rank representation of the stocks. In …

Blind Speaker Clustering, Ananth N. Iyer, Uchechukwu O. Ofoegbu, Robert E. Yantorno, Brett Y. Smolenski

Ananth N Iyer

A novel approach to performing speaker clustering in telephone conversations is presented in this paper. The method is based on a simple observation that the distance between populations of feature vectors extracted from different speakers is greater than a preset threshold. This observation is incorporated into the clustering problem by the formulation of a constrained optimization problem. A modified c-means algorithm is designed to solve the optimization problem. Another key aspect in speaker clustering is to determine the number of clusters, which is either assumed or expected as an input in traditional methods. The proposed method does not require such …

Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham

Theses and Dissertations

Identification of aircraft from high range resolution (HRR) radar range profiles requires a database of information capturing the variability of the individual range profiles as a function of viewing aspect. This database can be a collection of individual signatures or a collection of average signatures distributed over the region of viewing aspect of interest. An efficient database is one which captures the intrinsic variability of the HRR signatures without either excessive redundancy typical of single-signature databases, or without the loss of information common when averaging arbitrary groups of signatures. The identification of 'natural' clustering of similar HRR signatures provides a …