Applied Sciences

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18 pages, 7038 KiB

Open AccessArticle

A Novel ASIC Implementation of Two-Dimensional Image Compression Using Improved B.G. Lee Algorithm

by Tanya Mendez, Vishnumurthy Kedlaya K, Dayananda Nayak, H. S. Mruthyunjaya and Subramanya G. Nayak

Appl. Sci. 2023, 13(16), 9094; https://doi.org/10.3390/app13169094 - 9 Aug 2023

Cited by 2 | Viewed by 1583

Abstract

A 2D Discrete Cosine Transform and Inverse Discrete Cosine Transform using the B.G. Lee algorithm, incorporating a signed error-tolerant adder for additions, and a signed low-power fixed-point multiplier to perform multiplications are proposed and designed in this research. A novel Application Specific Integrated [...] Read more.

A 2D Discrete Cosine Transform and Inverse Discrete Cosine Transform using the B.G. Lee algorithm, incorporating a signed error-tolerant adder for additions, and a signed low-power fixed-point multiplier to perform multiplications are proposed and designed in this research. A novel Application Specific Integrated Circuit hardware implementation is used for the 2D DCT/IDCT computation of each 8 × 8 image block by optimizing the input data using the concepts of pipelining. An enhanced speed in processing and optimized arithmetic computations was observed due to the eight-stage pipeline architecture. The 2D DCT/IDCT of each 8 × 8 image segment can be quickly processed in 34 clock cycles with a substantially reduced level of circuit complexity. The B.G. Lee algorithm has been implemented using signed error-tolerant adders, signed fixed-point multipliers, and shifters, reducing computational complexity, power, and area. The Cadence Genus tool synthesized the proposed architecture with gpdk-90 nm and gpdk-45 nm technology libraries. The proposed method showed a significant reduction of 31.01%, 12.17%, and 21.11% in power, area, and PDP in comparison to the existing image compression architectures. An improved PSNR of the reconstructed image was also achieved compared to existing designs. Full article

(This article belongs to the Special Issue Advance in Digital Signal Processing and Its Implementation)

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17 pages, 2998 KiB

Open AccessArticle

An Efficient Algorithm and Architecture for the VLSI Implementation of Integer DCT That Allows an Efficient Incorporation of the Hardware Security with a Low Overhead

by Doru Florin Chiper and Arcadie Cracan

Appl. Sci. 2023, 13(12), 6927; https://doi.org/10.3390/app13126927 - 8 Jun 2023

Cited by 3 | Viewed by 1491

Abstract

In this paper, we propose a new hardware algorithm for an integer based discrete cosine transform (IntDCT) that was designed to allow an efficient VLSI implementation of the discrete cosine transform using the systolic array architectural paradigm. The proposed algorithm demonstrates multiple benefits [...] Read more.

In this paper, we propose a new hardware algorithm for an integer based discrete cosine transform (IntDCT) that was designed to allow an efficient VLSI implementation of the discrete cosine transform using the systolic array architectural paradigm. The proposed algorithm demonstrates multiple benefits specific to integer transforms with efficient hardware implementation and sufficient precision in approximating irrational transform coefficients for practical applications. The proposed integer DCT algorithm can be efficiently restructured into five regular and modular computational structures of lengths of four and one of length two called pseudo-cycle convolutions which translate into efficient VLSI implementations using systolic arrays. Moreover, besides an efficient VLSI implementation with high-speed performances due to the parallel decomposition of the proposed integer DCT algorithm, the proposed VLSI architecture uses a tag control mechanism that facilitates the integration of an obfuscation technique that significantly improves the hardware security with low overheads, maintaining all the implementation performances. Full article

(This article belongs to the Special Issue Advance in Digital Signal Processing and Its Implementation)

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14 pages, 1209 KiB

Open AccessCommunication

A Low-Complexity Channel Estimation Based on a Least-Squares Algorithm in OFDM Systems

by Yung-An Kao and Kun-Feng Wu

Appl. Sci. 2022, 12(9), 4258; https://doi.org/10.3390/app12094258 - 22 Apr 2022

Cited by 2 | Viewed by 1985

Abstract

As the channel frequency responses (CFRs) at virtual pilot subcarriers are assumed to be zero, the estimated CFRs will have a leakage effect for discrete Fourier transform (DFT)-based channel estimation in OFDM systems. The CFRs at odd pilot subcarriers and even pilot subcarriers [...] Read more.

As the channel frequency responses (CFRs) at virtual pilot subcarriers are assumed to be zero, the estimated CFRs will have a leakage effect for discrete Fourier transform (DFT)-based channel estimation in OFDM systems. The CFRs at odd pilot subcarriers and even pilot subcarriers are related if the number of maximum channel delay points is smaller than or equal to half the number of pilots (including virtual pilots). According to this correlation, we propose a low-complexity least-squares (LS) method to estimate the CFRs at virtual even and odd pilot subcarriers, respectively. This will solve the problem of the leakage effect in DFT-based channel estimation. The proposed method does not need to know the statistical properties of the channel or insert extra pilots as with some estimation methods. Furthermore, although this method has less computation than the LS method, both have almost the same channel estimation efficiency in simulation. The channel estimation efficiency of our proposed method is still similar to that of the LS method, even if the number of maximum channel delay points is greater than half the number of pilots. Therefore, the proposed low-complexity method is very suitable for equalizer hardware implementation. Full article

(This article belongs to the Special Issue Advance in Digital Signal Processing and Its Implementation)

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20 pages, 60601 KiB

Open AccessArticle

Broadband Spectral Analysis Algorithm with High-Frequency Resolution for Elimination of Overlap Interference between Adjacent Channels

by Xianhai Wang, Teng Wang, Chuan Yin, Jun Han, Qiao Meng and Chen Wang

Appl. Sci. 2021, 11(21), 10262; https://doi.org/10.3390/app112110262 - 1 Nov 2021

Cited by 2 | Viewed by 2551

Abstract

Spectral lines can be analysed to determine the physical properties of molecular clouds and the astrochemical processes in the formation area of massive stars. To improve the observation technology of radio astronomy, this paper proposes and compares two spectral analysis algorithms (improved weighted [...] Read more.

Spectral lines can be analysed to determine the physical properties of molecular clouds and the astrochemical processes in the formation area of massive stars. To improve the observation technology of radio astronomy, this paper proposes and compares two spectral analysis algorithms (improved weighted overlap-add (IWOLA) + FFT and IWOLA + weighted overlap-add (WOLA)). The proposed algorithms can obtain an ultra-high-frequency resolution for real-valued wideband signals, eliminate the signal overlapping interference between adjacent channels, substantially decrease the required hardware resources, especially multipliers, adders, and memory resources, and reduce the system design complexity. The IWOLA + FFT algorithm consists of an improved weighted overlap-add (IWOLA) filter bank, fast Fourier transform (FFT), a specific decimation for the output data from the IWOLA filter bank, and a selection for part of the output data from the FFT. The IWOLA + WOLA algorithm consists of the same modules as the IWOLA + FFT algorithm, with the second-stage FFT replaced by the modules of the weighted overlap-add (WOLA) filter bank and the accumulation for each sub-band. Based on an analysis of the underlying principles and characteristics of both algorithms, the IWOLA + FFT algorithm demonstrated a spectrum with a high frequency resolution and a comparable performance to an ultra-large-scale FFT, based on two smaller FFTs and a flexible architecture instead of a ultra-large-scale FFT. The IWOLA + WOLA algorithm contains the same function as the IWOLA + FFT algorithm and demonstrates a higher performance. The proposed algorithms eliminated the interference between the adjacent channels within the entire Nyquist frequency bandwidth. The simulation results verify the accuracy and spectral analysis performances of the proposed algorithms. Full article

(This article belongs to the Special Issue Advance in Digital Signal Processing and Its Implementation)

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16 pages, 2275 KiB

Open AccessArticle

Speckle Noise Detection and Removal for Laser Speech Measurement Systems

by Yahui Wang, Wenxi Zhang, Zhou Wu, Xinxin Kong and Hongxin Zhang

Appl. Sci. 2021, 11(21), 9870; https://doi.org/10.3390/app11219870 - 22 Oct 2021

Cited by 9 | Viewed by 2760

Abstract

Laser speech measurement is a new sound capture technology based on Laser Doppler Vibrometry (LDV). It avoids the need for contact, is easily concealed and is ideal for remote speech acquisition, which has led to its wide-scale adoption for military and security applications. [...] Read more.

Laser speech measurement is a new sound capture technology based on Laser Doppler Vibrometry (LDV). It avoids the need for contact, is easily concealed and is ideal for remote speech acquisition, which has led to its wide-scale adoption for military and security applications. However, lasers are easily affected by complex detection environments. Thus, speckle noise often appears in the measured speech, seriously affecting its quality and intelligibility. This paper examines all of the characteristics of impulsive noise in laser measured speech and proposes a novel automatic impulsive noise detection and removal method. This method first foregrounds noise using decorrelation based on a linear prediction (LP) model that improves the noise-to-signal ratio (NSR) of the measured signal. This makes it possible to detect the position of noise through a combination of the average short-time energy and kurtosis. The method not only precisely locates small clicks (with a duration of just a few samples), but also finds the location of longer bursts and scratches (with a duration of up to a hundred samples). The located samples can then be replaced by more appropriate samples whose coding is based on the LP model. This strategy avoids unnecessary processing and obviates the need to compromise the quality of the relatively large fraction of samples that are unaffected by speckle noise. Experimental results show that the proposed automatic speckle noise detection and removal method outperforms other related methods across a wide range of degraded audio signals. Full article

(This article belongs to the Special Issue Advance in Digital Signal Processing and Its Implementation)

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16 pages, 571 KiB

Open AccessArticle

Low-Complexity Recursive Least-Squares Adaptive Algorithm Based on Tensorial Forms

by Ionuț-Dorinel Fîciu, Cristian-Lucian Stanciu, Cristian Anghel and Camelia Elisei-Iliescu

Appl. Sci. 2021, 11(18), 8656; https://doi.org/10.3390/app11188656 - 17 Sep 2021

Cited by 7 | Viewed by 3443

Abstract

Modern solutions for system identification problems employ multilinear forms, which are based on multiple-order tensor decomposition (of rank one). Recently, such a solution was introduced based on the recursive least-squares (RLS) algorithm. Despite their potential for adaptive systems, the classical RLS methods require [...] Read more.

Modern solutions for system identification problems employ multilinear forms, which are based on multiple-order tensor decomposition (of rank one). Recently, such a solution was introduced based on the recursive least-squares (RLS) algorithm. Despite their potential for adaptive systems, the classical RLS methods require a prohibitive amount of arithmetic resources and are sometimes prone to numerical stability issues. This paper proposes a new algorithm for multiple-input/single-output (MISO) system identification based on the combination between the exponentially weighted RLS algorithm and the dichotomous descent iterations in order to implement a low-complexity stable solution with performance similar to the classical RLS methods. Full article

(This article belongs to the Special Issue Advance in Digital Signal Processing and Its Implementation)

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20 pages, 451 KiB

Open AccessArticle

An Insightful Overview of the Wiener Filter for System Identification

by Laura-Maria Dogariu, Jacob Benesty, Constantin Paleologu and Silviu Ciochină

Appl. Sci. 2021, 11(17), 7774; https://doi.org/10.3390/app11177774 - 24 Aug 2021

Cited by 14 | Viewed by 4862

Abstract

Efficiently solving a system identification problem represents an important step in numerous important applications. In this framework, some of the most popular solutions rely on the Wiener filter, which is widely used in practice. Moreover, it also represents a benchmark for other related [...] Read more.

Efficiently solving a system identification problem represents an important step in numerous important applications. In this framework, some of the most popular solutions rely on the Wiener filter, which is widely used in practice. Moreover, it also represents a benchmark for other related optimization problems. In this paper, new insights into the regularization of the Wiener filter are provided, which is a must in real-world scenarios. A proper regularization technique is of great importance, especially in challenging conditions, e.g., when operating in noisy environments and/or when only a low quantity of data is available for the estimation of the statistics. Different regularization methods are investigated in this paper, including several new solutions that fit very well for the identification of sparse and low-rank systems. Experimental results support the theoretical developments and indicate the efficiency of the proposed techniques. Full article

(This article belongs to the Special Issue Advance in Digital Signal Processing and Its Implementation)

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17 pages, 1545 KiB

Open AccessArticle

An Efficient Multistage Approach for Blind Source Separation of Noisy Convolutive Speech Mixture

by Junaid Bahadar Khan, Tariqullah Jan, Ruhul Amin Khalil, Nasir Saeed and Muhannad Almutiry

Appl. Sci. 2021, 11(13), 5968; https://doi.org/10.3390/app11135968 - 27 Jun 2021

Cited by 3 | Viewed by 2140

Abstract

This paper proposes a novel efficient multistage algorithm to extract source speech signals from a noisy convolutive mixture. The proposed approach comprises two stages named Blind Source Separation (BSS) and de-noising. A hybrid source prior model separates the source signals from the noisy [...] Read more.

This paper proposes a novel efficient multistage algorithm to extract source speech signals from a noisy convolutive mixture. The proposed approach comprises two stages named Blind Source Separation (BSS) and de-noising. A hybrid source prior model separates the source signals from the noisy reverberant mixture in the BSS stage. Moreover, we model the low- and high-energy components by generalized multivariate Gaussian and super-Gaussian models, respectively. We use Minimum Mean Square Error (MMSE) to reduce noise in the noisy convolutive mixture signal in the de-noising stage. Furthermore, the two proposed models investigate the performance gain. In the first model, the speech signal is separated from the observed noisy convolutive mixture in the BSS stage, followed by suppression of noise in the estimated source signals in the de-noising module. In the second approach, the noise is reduced using the MMSE filtering technique in the received noisy convolutive mixture at the de-noising stage, followed by separation of source signals from the de-noised reverberant mixture at the BSS stage. We evaluate the performance of the proposed scheme in terms of signal-to-distortion ratio (SDR) with respect to other well-known multistage BSS methods. The results show the superior performance of the proposed algorithm over the other state-of-the-art methods. Full article

(This article belongs to the Special Issue Advance in Digital Signal Processing and Its Implementation)

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