3 research outputs found

    An efficient hardware logarithm generator with modified quasi-symmetrical approach for digital signal processing

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    This paper presents a low-error, low-area FPGA-based hardware logarithm generator for digital signal processing systems which require high-speed, real time logarithm operations. The proposed logarithm generator employs the modified quasi-symmetrical approach for an efficient hardware implementation. The error analysis and implementation results are also presented and discussed. The achieved results show that the proposed approach can reduce the approximation error and hardware area compared with traditional methods

    Fixed-Point Implementations of the Reciprocal, Square Root and Reciprocal Square Root Functions

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    Implementations of the reciprocal, square root and reciprocal square root often share a common structure. This article is a survey and comparison of methods (with only slight variations for the three cases) for computing these functions. The comparisons are made in the context of the same accuracy target (faithful rounding) and of an arbitrary fixed-point format for the inputs and outputs (precisions of up to 32 bits). Some of the methods discussed might require some form of range reduction, depending on the input's range. The objective of the article is to optimize the use of fixed-size FPGA resources (block multipliers and block RAMs). The discussions and conclusions are based on synthesis results for FPGAs. They try to suggest the best method to compute the previously mentioned fixed-point functions on a FPGA, given the input precision. This work compares classical methods (direct tabulation, multipartite tables, piecewise polynomials, Taylor-based polynomials, Newton-Raphson iterations). It also studies methods that are novel in this context: the Halley method and, more generally, the Householder method

    A memory-efficient tables-and-additions method for accurate computation of elementary functions

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    The tables-and-additions methods for accurate computation of elementary functions are fast in computation speed but require large memory. A memory-efficient method named as the integrated Add-Table Lookup-Add (iATA) is proposed in this paper. In iATA, the mathematical formulation for computing the elementary functions is derived without using the central difference formulation to save memory. Three additional techniques, specifically the carry select technique, symmetry property exploitation and unequal partitioning of input with the aid of error analysis, are integrated in iATA to further reduce the memory size. The experimental results show that the proposed method is able to achieve higher memory efficiency than the best existing tables-and-additions methods. For the reciprocal and the natural logarithm function, iATA saves 23.63 and 61.39 percent of memory when compared to the best existing results obtained, respectively, by the unified Multipartite Table Method [39] and the Symmetric Table Addition Method [37]
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