Floating-point to fixed-point conversion with decision errors due to quantization

被引：0

作者：

Shi, CC ^{[1
]}

Brodersen, RW ^{[1
]}

机构：

[1] Univ Calif Berkeley, Dept EECS, Berkeley Wireless Res Ctr, Berkeley, CA 94720 USA

来源：

2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL V, PROCEEDINGS: DESIGN AND IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS INDUSTRY TECHNOLOGY TRACKS MACHINE LEARNING FOR SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING SIGNAL PROCESSING FOR EDUCATION | 2004年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Most existing analyses of quantization effects are given under the condition that all decision-making blocks, if exist in a system, produce identical decisions in both fixed-point and infinite-precision (IP) implementations. However, in doing floating-point to fixed-point conversion (FFC), a fixed-point design with occasional decision errors may still be an acceptable approximation of the IP system. We study the effect of this decision error, and relate its probability to the fixed-point data types. Our previous FFC methodology is then extended to include systems with possible decision errors due to quantization. The extended approach is applied to both CORDIC and BPSK transceiver.

引用

页码：41 / 44

页数：4

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