Improving Optimal Linear Associative Memory Using Data Partitioning

2006 ◽  
Author(s):  
Doosan Baek ◽  
Se-Young Oh
Keyword(s):  
Associative Memory ◽  
Data Partitioning ◽  
Optimal Linear ◽  
Using Data

Improved Data Partitioning for Building Large ROLAP Data Cubes in Parallel

2008 ◽  
pp. 3176-3193
Author(s):  
Ying Chen ◽  
Frank Dehne ◽  
Todd Eavis ◽  
A. Rau-Chaplin
Keyword(s):  
High Dimensional Data ◽  
Large Data ◽  
Data Partitioning ◽  
Data Cube ◽  
High Dimensional ◽  
Parallel Method ◽  
Data Cubes ◽  
Linear Speedup ◽  
Optimal Linear ◽  
Partitioning Technique

This paper presents an improved parallel method for generating ROLAP data cubes on a shared-nothing multiprocessor based on a novel optimized data partitioning technique. Since no shared disk is required, our method can be used for highly scalable processor clusters consisting of standard PCs with local disks only, connected via a data switch. Experiments show that our improved parallel method provides optimal, linear, speedup for at least 32 processors. The approach taken, which uses a ROLAP representation of the data cube, is well suited for large data warehouses and high dimensional data, and supports the generation of both fully materialized and partially materialized data cubes.

scholarly journals An Optimistic Data Mining Approach for Handling Large Data Set using Data Partitioning Techniques

2011 ◽  
Vol 24 (3) ◽  
pp. 29-33 ◽  
Author(s):  
Dipak V. Patil ◽  
R. S. Bichkar
Keyword(s):  
Data Mining ◽  
Large Data ◽  
Data Partitioning ◽  
Data Set ◽  
Data Mining Approach ◽  
Large Data Set ◽  
Using Data

SNR Scalability in H.264/AVC Using Data Partitioning

2006 ◽  
pp. 329-338 ◽  
Author(s):  
Stefaan Mys ◽  
Peter Lambert ◽  
Wesley De Neve ◽  
Piet Verhoeve ◽  
Rik Van de Walle
Keyword(s):  
Data Partitioning ◽  
Using Data

Enhanced Security in Cloud Using Data Partitioning Technique

2019 ◽  
Author(s):  
Taranpreet Singh Ruprah ◽  
Amol S Dange
Keyword(s):  
Data Partitioning ◽  
Using Data ◽  
Partitioning Technique

Mittag–Leffler synchronization for impulsive fractional-order bidirectional associative memory neural networks via optimal linear feedback control

2021 ◽  
Vol 26 (2) ◽  
pp. 207-226
Author(s):  
Jiazhe Lin ◽  
Rui Xu ◽  
Liangchen Li
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Associative Memory ◽  
Actuator Saturation ◽  
Sufficient Conditions ◽  
Linear Feedback ◽  
Impulsive Effect ◽  
Bidirectional Associative Memory ◽  
Optimal Linear ◽  
Predictor Corrector

In this paper, we are concerned with the synchronization scheme for fractional-order bidirectional associative memory (BAM) neural networks, where both synaptic transmission delay and impulsive effect are considered. By constructing Lyapunov functional, sufficient conditions are established to ensure the Mittag–Leffler synchronization. Based on Pontryagin’s maximum principle with delay, time-dependent control gains are obtained, which minimize the accumulative errors within the limitation of actuator saturation during the Mittag–Leffler synchronization. Numerical simulations are carried out to illustrate the feasibility and effectiveness of theoretical results with the help of the modified predictor-corrector algorithm and the forward-backward sweep method.

Efficient layered video coding using data partitioning

1999 ◽  
Vol 14 (9) ◽  
pp. 761-782 ◽  
Author(s):  
R Mathew ◽  
J.F Arnold
Keyword(s):  
Video Coding ◽  
Data Partitioning ◽  
Layered Video ◽  
Layered Video Coding ◽  
Using Data
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