Low power and real time very large scale integration （VLSI） architectures of motion estimation （ME） algorithms for mobile devices and applications are presented. The power reduction is achieved by devising a novel...Low power and real time very large scale integration （VLSI） architectures of motion estimation （ME） algorithms for mobile devices and applications are presented. The power reduction is achieved by devising a novel correction recovery mechanism based on algorithms which allow the use of reduced bit sum of absolute difference （RBSAD） metric for calculating matching error and conversion to full resolution sum of absolute difference （SAD） metric whenever necessary. Parallel and pipelined architectures for high throughput of full search ME corresponding to both the full resolution SAD and the generalized RBSAD algorithm are synthe- sized using Xilinx Synthesis Tools （XST）, where the ME designs based on reduced bit （RB） algorithms demonstrate the reduction in power consumption up to 45% and/or the reduction in area up to 38%.展开更多
There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing env...There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.展开更多
文摘Low power and real time very large scale integration （VLSI） architectures of motion estimation （ME） algorithms for mobile devices and applications are presented. The power reduction is achieved by devising a novel correction recovery mechanism based on algorithms which allow the use of reduced bit sum of absolute difference （RBSAD） metric for calculating matching error and conversion to full resolution sum of absolute difference （SAD） metric whenever necessary. Parallel and pipelined architectures for high throughput of full search ME corresponding to both the full resolution SAD and the generalized RBSAD algorithm are synthe- sized using Xilinx Synthesis Tools （XST）, where the ME designs based on reduced bit （RB） algorithms demonstrate the reduction in power consumption up to 45% and/or the reduction in area up to 38%.
文摘There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.
