Detecting Dependencies Between States of Multiple Data Streams

Abstract

The subject of dependency detection has been addressed many times during the last 20 years, and methods that extract frequent patterns or temporal information from data have been developed. The information extracted has been used in fields like medicine, network surveillance, stock analysis and many others, thus proving its importance in real life. But as technology evolved, the amount of generated information grew to the point where storing it for later analysis was no longer an option. In this paper we propose a method of temporal dependency detection between states of heterogeneous data streams, that processes the information as it arrives and discards it afterwards, and we test it on real surveillance data.

Authors and Affiliations

Stefan DRAGOS, Mircea VAIDA, Cristian URECHE, Loreta SUTA, Alin VOINA

Keywords

Related Articles

Test Power Optimization with Recordering of Genetic Test Vectors for VLSI Circuits

Power optimization is one of the important challenges in VLSI circuit for testing engineers. Larger power dissipation becomes the reason for overheating and with every increase in 10oC in operating temperature, failure r...

On The Choice Of The Method For Obtaining The Room Impulse Response

The paper presents an overview on the direct or indirect methods used to obtain the acoustic room impulse responses. The analysis of the most relevant methods is based on experimental measurements and the goal is to ach...

A Derived Robust Statistics Approach For Adaptive Volterra Filters Applied In Nonlinear Acoustic Echo Cancellation Scenarios

The paper proposes a novel updating concept for adaptive Volterra kernels that relies on a robust statistics approach. The optimization of a certain cost function leads to the update equations for the linear and quadrati...

Workflow Based Service Composition Using Genetic Algorithms

One common direction in service oriented computing is to use predefined workflows to compose new services that combine the functionality of existing services. But the problem with this approach is that services can’t be...

FPGA Implementation of LMS and NLMS adaptive filters for acoustic echo cancellation

The paper proposes a register transfer level (RTL) description of two well-known adaptive algorithms used in acoustic echo cancellation: the Least Mean Square (LMS) and Normalized Least Mean Square (NLMS). The RTL descri...

Download PDF file
  • EP ID EP87569
  • DOI -
  • Views 82
  • Downloads 0

How To Cite

Stefan DRAGOS, Mircea VAIDA, Cristian URECHE, Loreta SUTA, Alin VOINA (2013). Detecting Dependencies Between States of Multiple Data Streams. Acta Technica Napocensis- Electronica-Telecomunicatii (Electronics and Telecommunications), 54(1), 25-33. https://europub.co.uk/articles/-A-87569