Signal adaptive hardware implementation of a system for highly nonstationary two-dimensional FM signal estimation

Ivanovic, Veselin N.; Radovic, Nevena

doi:10.1016/j.aeue.2015.09.013

Cited by 21 publications

(25 citation statements)

References 30 publications

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“…x CTFWD n k L k L + + + element is imported to the matrix Q area, shifting to the right the existing matrix elements for one position, Fig.2, [1]. In this way, matrix Q slides for one position over frequency-onlydependent 2D CTFWD elements, creating the next basic FF region 1 2 ( , 1) k k Q + .…”

Section: The Rtl Design Methodology-based S/sf Optimal Filter Impmentioning

confidence: 99%

“…The FRS detection module generates FRS k by following the algorithm, initially considered in [9,10], but improved, realized and adapted for the case of highly nonstationary signals in [1]. It tests an LF existence in the FF point (k 1 ,k 2 ), Figure 2.…”

Section: The Rtl Design Methodology-based S/sf Optimal Filter Impmentioning

confidence: 99%

“…Sliding matrix operation file creates basic FF region from (3) and provides sliding of this region over the calculated 2D CTFWDs. Implementing the LF estimation procedure [1,9,10], the COMP block (set of comparators combined with the basic logic gates) tests an LF existence in the S/SF point lying outside bordering positions and corresponding to the central sliding matrix oparation file element. Based on (1) and the LF existence, it allows the corresponding 2D STFT element to participate in the ( )( ) Hx n creation.…”

Section: The Rtl Design Methodology-based S/sf Optimal Filter Impmentioning

confidence: 99%

“…It preserves optimal (2D WD) autoterms representation, but without cross-terms presence, [7,8], minimizes calculation complexity, [7,8], and simultaneously optimizes LF estimation characteristics in comparison to the other commonly used 2D S/SFDs, [8]. Therefore, in [1], the 2D CTFWD has been proposed as an optimal base for the optimal S/SF filter (1) development.…”

Section: Introductionmentioning

confidence: 98%

“…(4), are based on the same 2D STFT elements used in the 2D filtering definition (1) and have been already implemented in real-time, [5][6][7][8]. Therefore, real-time design of an optimal nonstationary 2D filter (1) can be developed (to estimate nonstationary 2D FM signal exposed to the high white noise) based on the some of available real-time designs (developed in [5][6][7][8] to provide the improved S/SF representation of input 2D noisy signal) and on the real-time algorithm for 2D CTFWD-based LF estimation, implemented through the sliding matrix operation, [1,9,10]. However, note that among all the S/SFDs, the 2D CTFWD, [7], shows same optimal characteristics.…”

Section: Introductionmentioning

confidence: 99%

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Local frequency estimation-based space/spatial-frequency optimal filter developed in the RTL design methodology versus the corresponding GPU-based implementations

Ivanovic

Radovic

Jovanovski

et al. 2015

2015 4th Mediterranean Conference on Embedded Computing (MECO)

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Processing of nonstationary one-dimensional and twodimensional (2D) signals are ussualy performed by using high numerically consuming time-frequency and space/spatialfrequency (S/SF) tools, respectively. Being numerically quite complex, these solutions require significant time for calculation and then are usually unsuitable for real-time analysis, but also their application is severely restricted in practice. Hardware implementations, when possible, can overcome these problems. Besides, numerical complexity greatly increases in the 2D signals case, so that demands for hardware implementations of systems for processing of these signals, including their filtering, are more emphasized. However, chip dimensions are significantly enlarged in this case, as well as the power consumption and cost, while the processing speed is seriously reduced. Therefore, having in mind technology limitations in hardware realizations, these systems usually cannot be implemented. To overcome these problems, the register transfer level (RTL) design methodology-based and signal adaptive development of the S/SF filter, suitable for realtime and on-a-chip implementation, has been designed in [1]. However, to significantly suppress time requirements of the space/spatial-frequency-based systems, the graphic processing units (GPUs)-based implementation of these systems can be considered as the possible solution. In this paper, the RTL design methodology-based solution from [1] is compared with the corresponding GPUs-based solutions.

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Section: The Rtl Design Methodology-based S/sf Optimal Filter Impmentioning

confidence: 99%

Section: The Rtl Design Methodology-based S/sf Optimal Filter Impmentioning

confidence: 99%

Section: The Rtl Design Methodology-based S/sf Optimal Filter Impmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Local frequency estimation-based space/spatial-frequency optimal filter developed in the RTL design methodology versus the corresponding GPU-based implementations

Ivanovic

Radovic

Jovanovski

et al. 2015

2015 4th Mediterranean Conference on Embedded Computing (MECO)

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show abstract

A new hardware architecture of the adaptive vector median filter and validation in a hardware/software environment

Atitallah

Abid

Boudabous

et al. 2021

Circuit Theory & Apps

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Presented in this paper is a new hardware architecture of the adaptive vector median filter (AVMF). The suggested structure yielded important values in impulsive noise removal from color images while preserving their fine details.The software (SW) study of this filter demonstrated that its implementation is too complex. To overcome this limitation, some approximations using a ROM memory were proposed to perform the square root for a hardware (HW) implementation. Comparative results between the ideal and approximated SWs of the AVMF showed a relative error equal to 0.01%. Then, sequential and parallel HW architectures were developed for this filter based on the approximated method. Finally, the validation of these architectures was conducted using an field-programmable gate array (FPGA) platform on an HW/SW environment. The validation results demonstrated that the proposed HW/SW implementation of the AVMF can speed up the execution time 180 times in the worst case at 140 MHz compared to the SW solution as well as preserving a high data quality (same image quality).

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A Step Toward Real-Time Time–Frequency Analyses with Varying Time–Frequency Resolutions: Hardware Implementation of an Adaptive S-transform

Radovic

Ivanovic

Djurović

et al. 2022

Circuits Syst Signal Process

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Signal adaptive hardware implementation of a system for highly nonstationary two-dimensional FM signal estimation

Cited by 21 publications

References 30 publications

Local frequency estimation-based space/spatial-frequency optimal filter developed in the RTL design methodology versus the corresponding GPU-based implementations

Local frequency estimation-based space/spatial-frequency optimal filter developed in the RTL design methodology versus the corresponding GPU-based implementations

A new hardware architecture of the adaptive vector median filter and validation in a hardware/software environment

A Step Toward Real-Time Time–Frequency Analyses with Varying Time–Frequency Resolutions: Hardware Implementation of an Adaptive S-transform

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