CVR: A Continuously Variable Rate LDPC Decoder Using Parity Check Extension for Minimum Latency

Pourjabar, Sina; Choi, Gwan

doi:10.1007/s11265-020-01597-0

Cited by 7 publications

(7 citation statements)

References 18 publications

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“…Future research will need to recognize the differences between two or more diseases and voice quality. Additionally, the author will constantly study the parameters that reflect important information about pathological voice signals to realize high classification performance using various deep learning methods and artificial intelligence (AI) techniques developed in various areas [31][32][33][34][35][36][37]. Finally, gender analysis in the field of pathological voice signal processing needs to become more widespread.…”

Section: Conflicts Of Interestmentioning

confidence: 99%

Experimental Evaluation of Deep Learning Methods for an Intelligent Pathological Voice Detection System Using the Saarbruecken Voice Database

Lee

2021

Applied Sciences

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This work is focused on deep learning methods, such as feedforward neural network (FNN) and convolutional neural network (CNN), for pathological voice detection using mel-frequency cepstral coefficients (MFCCs), linear prediction cepstrum coefficients (LPCCs), and higher-order statistics (HOSs) parameters. In total, 518 voice data samples were obtained from the publicly available Saarbruecken voice database (SVD), comprising recordings of 259 healthy and 259 pathological women and men, respectively, and using /a/, /i/, and /u/ vowels at normal pitch. Significant differences were observed between the normal and the pathological voice signals for normalized skewness (p = 0.000) and kurtosis (p = 0.000), except for normalized kurtosis (p = 0.051) that was estimated in the /u/ samples in women. These parameters are useful and meaningful for classifying pathological voice signals. The highest accuracy, 82.69%, was achieved by the CNN classifier with the LPCCs parameter in the /u/ vowel in men. The second-best performance, 80.77%, was obtained with a combination of the FNN classifier, MFCCs, and HOSs for the /i/ vowel samples in women. There was merit in combining the acoustic measures with HOS parameters for better characterization in terms of accuracy. The combination of various parameters and deep learning methods was also useful for distinguishing normal from pathological voices.

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Section: Conflicts Of Interestmentioning

confidence: 99%

Experimental Evaluation of Deep Learning Methods for an Intelligent Pathological Voice Detection System Using the Saarbruecken Voice Database

Lee

2021

Applied Sciences

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“…Obviously, in most cases, the necessity of designing an algorithm is to achieve several goals simultaneously. For example, the purpose of designing an algorithm could be to achieve high speed, adequate security, and high flexibility using various techniques such as Self-stabilizing techniques [28], [29], CNN method [30], [31], image and signal processing [32]- [34], hybrid methods [15] and so on, at the same time.…”

Section: Extraction Of Components 31 the Purposes Of Designing Cryptographic Algorithmsmentioning

confidence: 99%

Analysis of design goals of cryptography algorithms based on different components

Molk

Aref²,

Khorshid-Doust³

2021

IJEECS

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Cryptography algorithms are a fundamental part of a cryptographic system that is designed and implemented to increase information security. They are the center of attention of experts in the information technology domains. Although the cryptography algorithms are implemented to attainthe goals such as confidentially, integrity and authenticity of designing, but other matters that must be noticed by designers include speed, resource consumption, reliability, flexibility, usage type and so on. For the useful allocation of hardware, software, human resources, etc., it is important to identify the role of each of the factors influencing the design of cryptographic algorithms to invest in the development of cryptographic knowledge.This paper examines 1700 papers, documents and technical reports of international journals in the specific lengthy period (1978-2019), and the goal of the design and implementation of cryptography algorithms in a different period is extracted. Using a statistical population that consists of time and the number of documents in a long time and also avariety of data, leads this study to have a reliable result and attract the attention of designers.The results show that in recent years, attention tonew usage such as IoT and telemedicine, as well as lightweight cryptography, has increased to achieve the main goals.

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“…The relay is installed at the beginning, end of this line according to Fig. 1, and will adapt the required signals from the expected transmission line at any time [14].…”

Section: The Studied Gridmentioning

confidence: 99%

“…Because the presence of signal distortion causes the acquired features to lose their efficiency in separating the classes. Output accuracy will vary according to different values of signal to noise ratio (SNR) [14,15]. In this study, SNR values of 35 and 45 dB will be investigated [16].…”

Section: Classification Despite Noisy Datamentioning

confidence: 99%

Improving the Performance of Distance Relay Using Wavelet Transform

Mohabati

Khoddam

2021

Teh. glas. (Online)

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With proliferation of power grids, different types of faults are more likely to occur. The purpose of system protection relays is to detect abnormal signals that indicate faults in the transmission system and to separate the fault section from the rest of the system to prevent the fault from propagating to other parts of the system. Proliferation of electronic devices led to creation of digital relays made of microprocessors. Hence, analog measurements are converted into digital signals for processing by microprocessors. Air grids are more likely to cause faults than other components of the power system; thus, disturbances affecting the system must be detected quickly and accurately. Therefore, the problem of fault detection and classification is an important factor for economic exploitation of the power grid. Accurate fault handling results in faster repair operations, better system availability, lower operating costs and timesavings. The proposed design in this study was based on detecting the type of fault caused in transmission lines. In order to improve the condition of the relays in the transmission grid, analysis of the signals reached to the relay on both sides of the line was used to detect the fault and its type. The main purpose was to quickly detect the type of fault using wavelet transform. For this purpose, the signal was sampled after the fault occurs and the feature signal was extracted after analysis by wavelet transform. These features were included in the decision tree classifier and the type of the fault was decided.

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CVR: A Continuously Variable Rate LDPC Decoder Using Parity Check Extension for Minimum Latency

Cited by 7 publications

References 18 publications

Experimental Evaluation of Deep Learning Methods for an Intelligent Pathological Voice Detection System Using the Saarbruecken Voice Database

Experimental Evaluation of Deep Learning Methods for an Intelligent Pathological Voice Detection System Using the Saarbruecken Voice Database

Analysis of design goals of cryptography algorithms based on different components

Improving the Performance of Distance Relay Using Wavelet Transform

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