Showing papers on "Harmonic wavelet transform published in 2019"
TL;DR: This paper uses the higher-order-logic based formalizations of differential, integral, transcendental and topological theories of multivariable calculus to formally define Fourier transform and reason about the correctness of its classical properties, such as existence, linearity, time shifting, frequency shifting, modulation, time scaling, time reversal and differentiation in time domain.
10 citations
TL;DR: An adaptive complex harmonic discrete wavelet transform with an advanced statistical method is implemented to overcome the shortcomings of the classical wavelet method and effectively eliminates the bird contamination even where the classical method fails.
Abstract: Boundary layer radar (L-band) wind profilers frequently encounter a significant problem arising from the contamination of intermittent clutter, produced by seasonal and nocturnal migrating birds, which often yields erroneous wind velocity and boundary layer information. Classical harmonic wavelet transforms (HWTs) are inadequate in removing the transient clutter contamination under certain conditions, particularly when the clutter is significant. We implemented an adaptive complex harmonic discrete wavelet transform with an advanced statistical method to overcome the shortcomings of the classical wavelet method. This algorithm effectively eliminates the bird contamination even where the classical method fails. Finally, a multiple peak-picking (MPP) algorithm was added to select true atmospheric signals and estimate accurate moments. The obtained wind velocity measurements were compared with those derived using the conventional method and validated with global positioning system radiosonde winds. The comparison shows that the proposed method is more effective than the conventional one.
8 citations
TL;DR: A performance evaluation of color images and its comparison with the recently proposed approaches, using the modified technique already proposed for grayscale images, by the authors.
Abstract: Abstract Steganography is the foremost influential approach to hide data. Images serve as the most appropriate cover media for steganography. This paper intends to do a performance evaluation of color images and its comparison with the recently proposed approaches, using the modified technique already proposed for grayscale images, by the authors. This approach hides large data in color image using the blocking concept. The blocking process is applied on approximation coefficients of secret image and detail coefficients of red, green and blue components of cover image. The blocks of detail coefficients are replaced with approximation coefficients of secret image using root mean square error method. The key is used to store the position of best matching blocks. It is being predicated that the work will be able to hide large data in a single image. The stego image (ST) has better visual quality based on the peak signal to noise ratio values.
8 citations
01 Jan 2019
TL;DR: This chapter first presents Lie operators for key points detection working in the affine plane, stimulated by certain evidence of the human visual system and appears to be very useful for implementing in near future of an humanoid vision system.
Abstract: This chapter first presents Lie operators for key points detection working in the affine plane. This approach is stimulated by certain evidence of the human visual system; therefore, these Lie filters appear to be very useful for implementing in near future of an humanoid vision system.
3 citations
01 Apr 2019
TL;DR: Proposed current based scheme proved to be effective in detection and classification of transmission line faults to provide efficient protection to line.
Abstract: This paper presents an algorithm to provide current based scheme for protection of transmission line. The proposed algorithm is implemented using harmonic wavelet transform (HWT) and rule based decision tree. Current measured on two ends of transmission line has been decomposed using harmonic wavelet transform. Absolute values of output of harmonic wavelet transform based decomposition of current signal is taken as fault index and plotted for recognition of faults. Peak values of the fault indexes are used as input data to rule based decision tree to classify faults. Proposed current based scheme proved to be effective in detection and classification of transmission line faults to provide efficient protection to line.
2 citations
31 Oct 2019
TL;DR: A simple and computationally efficient WT, harmonic wavelet transform, for OFDM signal processing is introduced and it is shown that the proposed HW-OFDM is better in terms of peak-to-average power ratio reduction.
Abstract: Orthogonal frequency-division multiplexing (OFDM) is a popular multi-carrier technique used in many digital communication systems such as wireless fidelity (Wi-Fi), long term evolution (LTE) and power line communication systems. It can be designed using fast Fourier transform (FFT) or wavelet transform (WT). The major drawback in using WT is that it is computationally inefficient. In this study, we introduce a simple and computationally efficient WT, harmonic wavelet transform, for OFDM signal processing. The new WT uses the orthogonal basis functions of conventional FFT-OFDM except that it involves translation and dilation of the input signal; the new wavelets is referred to as harmonic wavelets (HW). When compared with pilot-assisted OFDM system in terms of reduction in the peak-to-average power ratio, the results show that HW-OFDM outperforms FFT-OFDM by 3 dB at 10−4 CCDF (complementary cumulative distribution function). Over Rayleigh fading channel with additive white Gaussian noise (AWGN), the bit error ratio of both FFT-OFDM and HW-OFDM perfectly matched, showing that the proposed HW-OFDM is better in terms of peak-to-average power ratio reduction.
1 citations