Performance Comparison of FFT, DCT, DWT and DDDWT-OFDM in Rayleigh Channel

Rani, D. Leela; Bharathi, M.; Padmaja, N.

doi:10.1109/icssit46314.2019.8987953

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…The application of Discrete Wavelet Transform (DWT) and Wavelet Scattering in the analysis of vibrational signals in dynamic systems has made significant advancements, replacing conventional methods such as the Fast Fourier Transform (FFT) [1] [2]. These techniques have proven to be robust and effective in fault detection and system analysis, especially when combined with classifiers like Long Short-Term Memory (LSTM) and Support Vector Machines (SVM) [3], [4].…”

Section: Introductionmentioning

confidence: 99%

investigation into vibration analysis for detecting faults in vehicle steering outer tie-rod

Alaraji,

Alp

2024

Acta IMEKO

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This study presents a novel fault detection method in car gear steering systems, employing MSC Adams and MATLAB simulations to analyze angular acceleration from the outer tie rod. The approach closely mimics real accelerometer data to differentiate between normal and faulty conditions, including wear and obstacle navigation. Emphasis is on noise robustness, utilizing advanced noise injection and denoising techniques. The efficacy of wavelet scattering, discrete wavelet transform (DWT) methods, and classifiers like Support Vector Machines (SVM) and Neural Networks (NN) is extensively evaluated. Among fifteen fault detection methods, the combination of wavelet scattering with Long Short-Term Memory (LSTM) Neural Networks, optimized with Adam tuning, is notably stable across four scenarios. The research highlights the importance of precise feature selection, employing techniques like Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Recursive Feature Elimination (RFE). This research significantly advances the reliability of autonomous driving systems and provides essential insights into fault detection in gear steering systems.

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Section: Introductionmentioning

confidence: 99%

investigation into vibration analysis for detecting faults in vehicle steering outer tie-rod

Alaraji,

Alp

2024

Acta IMEKO

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“…Research of various algorithms on computational complexity reduction in OFDM has been investigating. The performance of Discrete Wavelet Transform (DWT), Double Density Discrete Wavelet Transforms (DDDWT), Discrete Cosine MOD Transform (DCT) that applied to OFDM have been studied in [17]- [24]. Also, the use of various FFT algorithms as 2-radix FFT, 4-radix FFT, Winograd FFT, and the very recent very fast Fourier transform (VFFT) in the OFDM system have been examined in [25]- [29].…”

Section: Introductionmentioning

confidence: 99%

G-OFDM Variants Evaluation for Transmitter and Receiver Implementation

Wirastuti¹,

Noras²

2021

International Journal on Advanced Science, Engineering and Information Technology

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Orthogonal Frequency Division Multiplexing (OFDM) is chosen as a multiplexing technique and broadly used in today's radiocommunication environments to overcome spectrum insufficiency. In current OFDM applications, the IDFT/DFT algorithms are used for modulation and demodulation, efficiently implemented using the IFFT/FTT. The IFFT and FFT are some of the main components of OFDM systems, requiring intensive computation, especially for a high number of sub-channels. Reducing the computational burden of the IFFT/FFT would offer an advantage in reducing the total OFDM system complexity. In this proposed system, the idea of implementing the very fast Fourier transform (VFFT) in OFDM (later, it is called G-OFDM) is based on a trade-off between performance and complexity. The implementation complexity of G-OFDM is lower than OFDM. However, there is a performance cost. G-OFDM has been studied both analytically and in simulation over the AWGN channel. In particular, performance is marred by the non-uniformity of SNR among sub-carriers. In this study, it was proposed two G-OFDM variants called G1-OFDM and G2-OFDM. G1-OFM is the least complex among all G-OFDM scenarios but gives the worst performance, while G2-OFDM gives the best performance but is the most complex. The results show that the performance of G-OFDM and its variants can be improved through the application of different values of n-quantization levels. In other words, using n-quantization levels, we can decrease the processing loss of the G system.

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