Adaptive Bivariate Function Generation based on Chebyshev-Polynomials

被引：0
|
作者：
Rust, Jochen [1 ]
Seidel, Pascal [1 ]
Paul, Steffen [1 ]
机构：
[1] Univ Bremen, Inst Electrodynam & Microelect ITEMme, Bremen, Germany
来源：
2019 17TH IEEE INTERNATIONAL NEW CIRCUITS AND SYSTEMS CONFERENCE (NEWCAS) | 2019年
关键词：
function generator; numeric function approximation; Chebyshev-Polynomials;
D O I：
10.1109/newcas44328.2019.8961270
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper an adaptive hardware architecture for high-performance bivariate numerical function approximation is presented. Orthogonal Chebyshev-Polynomials are exploited that cover incremental accuracy refinements. Additionally, switching between two numeric functions is easily deployable by changing the set of polynomial coefficients. For evaluation, different configurations of the proposed hardware function generator are implemented and analyzed considering three bivariate numeric functions. The resulting performance highlights this approach to be a powerful extension for bivariate function approximation.
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页数：4
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