Abstract
Development and improvement of a mathematical model for a large-scale analysis based on the Daubechies discrete wavelet transform will be implemented in an algebraic system possessing a property of ring and field suitable for speech signals processing. Modular codes are widely used in many areas of modern information technologies. The use of these non-positional codes can provide high-speed data processing. Therefore, these algebraic systems should be used in the algorithms of digital processing of signals, which are characterized by processing large amounts of data in real time. In addition, modular codes make it possible to implement large-scale signal processing using the wavelet transform. The paper discusses examples of the Daubechies wavelet transform application. Integer processing, presented in the paper, will reduce the number of rounding errors when processing the speech signals.
Highlights
Increasing the productivity of computer systems by reducing the size of the element base of computer technology at the current level of technology development is problematic
We will develop a mathematical model for a large-scale analysis based on the Daubechies discrete wavelet transform, which will be implemented in an algebraic system possessing a property of ring and field [5]
The matrix associated with this set of filters is: We will develop a mathematical model for a large-scale analysis based on the Daubechies discrete wavelet transform, which will be implemented in an algebraic system possessing a property of ring
Summary
Increasing the productivity of computer systems by reducing the size of the element base of computer technology at the current level of technology development is problematic In this regard, the problem of parallel data processing is a promising direction. The use of low-bit numbers in the RNS calculations can significantly reduce power consumption of digital devices [1]. It is useful for the synthesis of RNS computing facilities with a parallel structure, like FPGA (Field-Programmable Gate Array) or ASIC We propose a new approach to overcome the difficulty of complex computation, based on the use of finite field wavelets in RNS. The absence of this is a drawback when performing a transformation in the target field
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