A note on digital filter synthesis

Gold, B.; Jordan, K.

doi:10.1109/proc.1968.6709

Cited by 74 publications

(10 citation statements)

References 2 publications

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“…Instead, we know state the third important property of z-transforms viz. that if equation (20) is true, then so is,…”

Section: Z-transformmentioning

confidence: 98%

“…A very common mistake that has been perpetuated in the literature is to identify FIR with non ·recursive and IIR with recursive. As pointed out by Gold and Jordan (1968), the term recursive and non-recursive should be used only to describe the method of realization. A realization in which no past values of the output have to be called back to compute the present output is called non-recursive ; if one or more past values of the output are required for computing the present value of the output, the realization is called recursive.…”

Section: (25)mentioning

confidence: 99%

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The ABCD's of Digital Signal Processing (Part 1)

Roy

1980

IETE Journal of Education

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In this article, the basic concepts of digital signal processing will be introduced, leading to a mathematical description of a digital signal processor in terms of, first, a difference equation and, second, a z-domain transfer function. In the process, the effects of sampling and quantization will be brieHy touched upon. Implementation of a processor by special purpose hardware and discrete Fourier transform technique will be discussed. The Fast Fourier Transform (FFT) will be introduced and several of. its applications will be presented, along with the pitfalls and incorrect usage of the tecbnique.t

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“…Instead, we know state the third important property of z-transforms viz. that if equation (20) is true, then so is,…”

Section: Z-transformmentioning

confidence: 98%

Section: (25)mentioning

confidence: 99%

The ABCD's of Digital Signal Processing (Part 1)

Roy

1980

IETE Journal of Education

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“…This realization can be written as The realization of both FIR filters and IIR filters can be performed using nonrecursive and recursive methods [11], [12]. However it is worth to mention here that, usually nonrecursive realizations of FIR filters and recursive realizations of IIR filters are most efficient and are in generally used.…”

Section: Nonrecursive Realizationmentioning

confidence: 99%

FPGA Implementation of Higher Order FIR Filter

Singh¹,

Prakash

2017

IJECE

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The digital Finite-Impulse-Response (FIR) filters are mainly employed in digital signal processing applications. The main components of digital FIR filters designed on FPGAs are the register bank to save the samples of signals, adder to implement sum operations and multiplier for multiplication of filter coefficients to signal samples. Although, design and implementation of digital FIR filters seem simple but the design bottleneck is multiplier block for speed, power consumption and FPGA chip area occupation. The multipliers are an integral part in FIR structures and these use a large part of the chip area. This limits the number of processing elements (PE) available on the chip to realize a higher order of filter. A model is developed in the Matlab/Simulink environment to investigate the performance of the desired higher order FIR filter. An equivalent FIR filter representation is designed by the Xilinx FIR Compiler by using the exported FIR filter coefficients. The Xilinx implementation flow is completed with the help of Xilinx ISE 14.5. It is observed how the use of higher order FIR filter impacts the resource utilization of the FPGA and it's the maximum operating frequency. Keyword:Fir filter FPGA Higher order fir filter Xilinx

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“…In 1968, the linear recurrences methodology was applied for the first time in the DSP domain [10]. Soon it was applied on a variety of signal processing problems [3], [37].…”

Section: Prior Artmentioning

confidence: 99%

“…The maximally fast implementation of linear computation is a widely applicable topic which has not been studied previously. There is a number of techniques which provide arbitrarily fast implementations for various classes of computations [9], [10], [24], [37]. The new arbitrarily fast solution maintains asymptotically the AT product constant and, hence, is more hardware efficient than any of the previously proposed techniques.…”

Section: Prior Artmentioning

confidence: 99%

Maximally and arbitrarily fast implementation of linear and feedback linear computations

Potkonjak

Rabaey

2000

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Abstract-By establishing a relationship between the basic properties of linear computations and eight optimizing transformations (distributivity, associativity, commutativity, inverse and zero element law, common subexpression replication and elimination, constant propagation), a computer-aided design platform is developed to optimally speed-up an arbitrary instance from this large class of computations with respect to those transformations. Furthermore, arbitrarily fast implementation of an arbitrary linear computation is obtained by adding loop unrolling to the transformations set. During this process, a novel Horner pipelining scheme is used so that the area-time (AT) product is maintained constant, regardless of achieved speed-up. We also present a generalization of the new approach so that an important subclass of nonlinear computations, named feedback linear computations, is efficiently, maximally, and arbitrarily sped-up.Index Terms-Digital signal processing (DSP), high-level synthesis, Horner scheme, linear computations, throughput, transformations, very large scale integrated circuit (VLSI) design.

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A note on digital filter synthesis

Cited by 74 publications

References 2 publications

The ABCD's of Digital Signal Processing (Part 1)

The ABCD's of Digital Signal Processing (Part 1)

FPGA Implementation of Higher Order FIR Filter

Maximally and arbitrarily fast implementation of linear and feedback linear computations

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