- We will send in 10–14 business days.
/images/books/13457605/9783960671558.jpg)
- Author: B Vinoth Kumar
- Publisher: Anchor Academic Publishing
- Year: 2017
- ISBN-10: 3960671555
- ISBN-13: 9783960671558
- Format: 14.8 x 21 x 0.4 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
The Floating Point Multiplier is a wide variety for increasing accuracy, high speed and high performance in reducing delay, area and power consumption. The floating point is used for algorithms of Digital Signal Processing and Graphics. Many floating point multipliers are used to reduce the area that perform in both the single precision and the double precision in multiplication, addition and subtraction. Here, the scientific notations sign bit, mantissa and exponent are used. The real numbers are divided into two components: fixed component of significant range (lack of dynamic range) and exponential component in floating point (largest dynamic range). The authors convert decimal to floating point and normalize the exponent part and rounding operation to reduce latency. The mantissa of two values are multiplied and the exponent part is added. The sign results with exclusive-or are obtained. Then, the final result of shift and add floating point multiplier is compared with booth multiplication.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 20d.20:56:42
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: B Vinoth Kumar
- Publisher: Anchor Academic Publishing
- Year: 2017
- ISBN-10: 3960671555
- ISBN-13: 9783960671558
- Format: 14.8 x 21 x 0.4 cm, softcover
- Language: English English
The Floating Point Multiplier is a wide variety for increasing accuracy, high speed and high performance in reducing delay, area and power consumption. The floating point is used for algorithms of Digital Signal Processing and Graphics. Many floating point multipliers are used to reduce the area that perform in both the single precision and the double precision in multiplication, addition and subtraction. Here, the scientific notations sign bit, mantissa and exponent are used. The real numbers are divided into two components: fixed component of significant range (lack of dynamic range) and exponential component in floating point (largest dynamic range). The authors convert decimal to floating point and normalize the exponent part and rounding operation to reduce latency. The mantissa of two values are multiplied and the exponent part is added. The sign results with exclusive-or are obtained. Then, the final result of shift and add floating point multiplier is compared with booth multiplication.
Reviews