1996
DOI: 10.1109/82.486455
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Area-efficient multipliers for digital signal processing applications

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Cited by 141 publications
(67 citation statements)
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“…Applications Such as DSP, image processing and multimedia require extensive use of multiplication and squaring functions (Sheu and Lin, 2002;Walters et al, 2003). In many DSP processing algorithms such as digital filters, Discrete Cosine Transform (DCT) and wavelet transform, it is desirable to provide full precision multiplication and fixed width multiplication (Lim, 1992;Schulte and Swartzlander, 1993;Kidambi et al, 1996;Swartzlander, 1999;Van et al, 2000;Van and Yang, 2005) that produces n-bit output product with n-bit multiplier and n-bit multiplicand with low error. If the product is truncated to n-bits, the least-significant columns of the product matrix contribute little to the final result.…”
Section: Introductionmentioning
confidence: 99%
“…Applications Such as DSP, image processing and multimedia require extensive use of multiplication and squaring functions (Sheu and Lin, 2002;Walters et al, 2003). In many DSP processing algorithms such as digital filters, Discrete Cosine Transform (DCT) and wavelet transform, it is desirable to provide full precision multiplication and fixed width multiplication (Lim, 1992;Schulte and Swartzlander, 1993;Kidambi et al, 1996;Swartzlander, 1999;Van et al, 2000;Van and Yang, 2005) that produces n-bit output product with n-bit multiplier and n-bit multiplicand with low error. If the product is truncated to n-bits, the least-significant columns of the product matrix contribute little to the final result.…”
Section: Introductionmentioning
confidence: 99%
“…In order to reduce the truncation error, many error compensation methods for fixed-width multipliers have been proposed in [4,5,6,7]. Error compensation biases of these methods can be classified into constant biases [4] and adaptive biases (or, data dependant biases) [5,6,7]. A constant bias is generated independent of the truncated partial products bits and is fixed for a given input word size.…”
Section: Introductionmentioning
confidence: 99%
“…Tables 1, 2 and 3 show simulated results for various fixed-width multipliers at different width s . The comparison results show that our proposed fixed-width multipliers are more accurate than others [2][3][4][5][6][7] for different values of w . The better performance is achieved due to the fact that we derive better error-compensation biases to reduce truncation error.…”
Section: Performance Discussionmentioning
confidence: 84%
“…The better performance is achieved due to the fact that we derive better error-compensation biases to reduce truncation error. The area-ratio in Table 4 shows that the proposed multiplier has nearly the same area-ratio as that of [4][5][6][7] at each value of w so that the lower-error fixed-width multiplier is area-efficient. Next, we apply the proposed fixed-width multiplier to the 35-tap FIR filter for speech processing.…”
Section: Performance Discussionmentioning
confidence: 98%
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