Polynomial-based filters with odd number of polynomial segments for interpolation

Babić, Djordje; ghadam, Ali Shahed hagh; Renfors, Markku

doi:10.1109/lsp.2003.821681

Cited by 7 publications

(6 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the decimation factor 1/R or the interpolation factor R is an integral value, then the conversion of sampling rate can be performed conveniently with the aid of fixed digital filters [8]. In case of a scenario where the factors are irrational, it will be impossible to use fixed digital filters directly.…”

Section: F Filters With Non Integer Decimation Factor: Farrow Filtersmentioning

confidence: 99%

“…In case of a scenario where the factors are irrational, it will be impossible to use fixed digital filters directly. Moreover, if R is considered as the ratio of two relatively large prime integers, then, in the case of the conventional poly-phase implementation, it is quiet essential that the orders of the required filter become very large [8]. It means that a large number of coefficients need to be stored in coefficient memory.…”

Section: F Filters With Non Integer Decimation Factor: Farrow Filtersmentioning

confidence: 99%

“…Among them, polynomial-based filters are generally assumed to provide an efficient implementation form directly in digital domain. Such filters witness an effective implementation through Farrow structure or its higher version [8]- [13]. The main advantage of the Farrow structure is based on the presence of fixed finite-impulse response (FIR) filters as one of its ingredients.…”

Section: F Filters With Non Integer Decimation Factor: Farrow Filtersmentioning

confidence: 99%

See 2 more Smart Citations

Efficient Implementation of Sample Rate Converter

Singh¹,

Patterh²,

Sharma³

2010

IJACSA

View full text Add to dashboard Cite

Abstract-Within wireless base station system design, manufacturers continue to seek ways to add value and performance while increasing differentiation. Transmit/receive functionality has become an area of focus as designers attempt to address the need to move data from very high frequency sample rates to chip processing rates. Digital Up Converter (DUC) and Digital Down Converter (DDC) are used as sample rate converters. These are the important block in every digital communication system; hence there is a need for effective implementation of sample rate converter so that cost can be reduced. With the recent advances in FPGA technology, the more complex devices providing high-speed as required in DSP applications are available. The filter implementation in FPGA, utilizing the dedicated hardware resources can effectively achieve application-specific integrated circuit (ASIC)-like performance while reducing development time cost and risks. So in this paper the technique for an efficient design of DDC for reducing sample rate is being suggested which meets the specifications of WiMAX system. Its effective implementation also ensures the pathway for the efficient applications in VLSI designs. Different design configurations for the sample rate converter are explored. The sample rate converter can be designed using half band filters, fixed FIR filters, poly-phase filters, CIC filters or even farrow filters.

show abstract

Section: F Filters With Non Integer Decimation Factor: Farrow Filtersmentioning

confidence: 99%

Section: F Filters With Non Integer Decimation Factor: Farrow Filtersmentioning

confidence: 99%

Section: F Filters With Non Integer Decimation Factor: Farrow Filtersmentioning

confidence: 99%

See 1 more Smart Citation

Efficient Implementation of Sample Rate Converter

Singh¹,

Patterh²,

Sharma³

2010

IJACSA

View full text Add to dashboard Cite

show abstract

“…As examples, Figures 8a and b show the magnitude responses of the Lagrange 26+3β (1) The length of the prefilter is 11. When exploiting the coefficient symmetries, six multipliers are required.…”

Section: Examplesmentioning

confidence: 99%

“…[20]. 1 Tampere, Finland. E-mail: ts@cs.tut.fi continuous-valued input parameter, called the fractional interval, which can be used to control the time instant for the output sample.…”

Section: Introductionmentioning

confidence: 99%

Polynomial-Based Interpolation Filters—Part I: Filter Synthesis

Vesma

Saramäki

2007

Circuits Syst Signal Process

View full text Add to dashboard Cite

This paper introduces a generalized design method for polynomial-based interpolation filters. These filters can be implemented by using a modified Farrow structure, where the fixed finite impulse response (FIR) sub-filters possess either symmetrical or anti-symmetrical impulse responses. In the proposed approach, the piecewise polynomial impulse response of the interpolation filter is optimized directly in the frequency domain using either the minimax or least mean square criterion subject to the given time domain constraints. The length of the impulse response and the degree of the approximating polynomial in polynomial intervals can be arbitrarily selected. The optimization in the frequency domain makes the proposed design scheme more suitable for various digital signal processing applications and enables one to synthesize interpolation filters for arbitrary desired and weighting functions. Most importantly, the interpolation filters can be optimized in a manner similar to that of conventional linear-phase FIR filters.

show abstract