Fast and Accurate Approximation Methods for Trigonometric and Arctangent Calculations for Low-Performance Computers

In modern computers, complicated signal processing is highly optimized with the use of compilers and high-speed processing using floating-point units (FPUs); therefore, programmers have little opportunity to care about each process. However, a highly accurate approximation can be processed in a smal...

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Bibliographic Details
Published in:Electronics Vol. 11; no. 15; p. 2285
Main Authors: Kusaka, Takashi, Tanaka, Takayuki
Format: Journal Article
Language:English
Published: Basel MDPI AG 22.07.2022
Subjects:
algorithm design and analysis
Algorithms
Approximation
arctangent approximation
arctangent approximation; trigonometric functions approximation; elemental function approximation; fused multiply–add; algorithm design and analysis; computational cost reduction
Attitude control
Compilers
Computation
computational cost reduction
Digital signal processors
elemental function approximation
Embedded systems
Field programmable gate arrays
Floating point arithmetic
fused multiply-add
Graphics processing units
Machine learning
Mathematical analysis
Microcontrollers
Multiplication & division
Performance evaluation
Power consumption
Power management
Robot control
Signal processing
Trigonometric functions
trigonometric functions approximation
ISSN:2079-9292, 2079-9292
Online Access:Get full text
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Summary:In modern computers, complicated signal processing is highly optimized with the use of compilers and high-speed processing using floating-point units (FPUs); therefore, programmers have little opportunity to care about each process. However, a highly accurate approximation can be processed in a small number of computation cycles, which may be useful when embedded in a field-programmable gate array (FPGA) or micro controller unit (MCU), or when performing many large-scale operations on a graphics processing unit (GPU). It is necessary to devise algorithms to obtain the desired calculated values without an accelerator or compiler assistance. The residual correction method (RCM) developed here can produce simple and accurate approximations of certain nonlinear functions with minimal multiply–add operations. In this study, we designed an algorithm for the approximate computation of trigonometric and inverse trigonometric functions, which are nonlinear elementary functions, to achieve their fast and accurate computation. A fast first approximation and a more accurate second approximation of each function were created using RCM with a less than 0.001 error using multiply–add operations only. This achievement is particularly useful for MCUs, which have a low power consumption but limited computational power, and the proposed approximations are candidate algorithms that can be used to stabilize the attitude control of robots and drones, which require real-time processing.
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ISSN:2079-9292
2079-9292
DOI:10.3390/electronics11152285