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This paper presents an affine approximation method for multiplication, which achieves better trade-off between accuracy and computational complexity.

This paper presents a novel affine approximation method for multiplication, Approximation Affine based on Space Extreme Estimation.

Rodrigues (2006) derived the adjoint equations in a much neater way, and provided a method for multiplication of a vector by the sensitivity matrix or its transpose.

Our project has demonstrated the efficiency of Urdhava-Tiryagbhyam method for multiplication which conveys a distinction in the real procedure of multiplication itself.

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The latter contains three treatises, Chengchu tongbian benmo (1274; "Fundament and Periphery for Continuity and Change in Multiplication and Division"), Tianmu bilei chengchu jiefa (1275; "Quick Methods for Multiplication and Division in Surveying and Analogous Categories"), and Xu gu zhai qi suan fa (1275; "Selection of Strange Mathematical Methods in Continuation of Antiquity").

Further speed comparisons of compressor adders with traditional ones and proposed multiplier with popular methods for multiplication are shown.

To analyze the uncertainty conveniently, we use two parts to divide the different parts of all the approximation methods for multiplication, which include AATRE, AACHA, and AASEE.

To solve this problem, Stolfi and de Figueiredo [22] proposed affine approximation methods for multiplication, which include trivial range estimation (AATRE) and Chebyshev approximation (AACHA).

Although modern plantations are often composed of clones (grafted trees or rooted cuttings), propagation by seed has been the simple traditional method for the multiplication of cacao trees.

Figure 4 shows the FrFT spectrogram using this method for a multiplication of FrFT orders from 1 to 10. Figure 4 FFT-based (a) and FrFT-based ((b); multiorder multiplication, ) spectrograms of the vowel.

Simulation results show that the proposed IOD method for logarithmic multiplication without the pipelining gives maximum of 35.39% less ADP and 11.15% less EPS for 32-bit architecture than of the reported logarithmic multiplier architecture.

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