Use Of Fractional Fourier Transform Research Articles

3D palatal rugae recognition based on Fractional Fourier Transform

Following a major disaster, most of the biological characteristics of the victims are typically destroyed, which increases the difficulty of forensic identification. However, palatal rugae cannot be easily destroyed owing to its unique location characteristics, owing to which it has become a new type of biological feature used in forensic identification under special environments. This study proposes a new method of 3D palatal rugae recognition which uses fractional Fourier transform (FRFT). The isometric slicing operation is first used to simplify the complexity of the algorithm and improve the efficiency of the 3D data storage and expression. FRFT is the used to extract the fractional domain features of the profile images obtained by slicing the 3D palatal rugae, and the support vector machine recursive feature elimination (SVM-RFE) method is used for feature selection in the fractional domain. The use of FRFT increases the number of the palatal rugae features extracted from the time-frequency domain, and can improve the effectiveness of feature extraction. The recognition accuracy rate of the proposed 3D palatal rugae recognition system can reach up to 97.8%. The proposed method meets the requirements of 3D palatal rugae recognition, and can help in performing rapid forensic identification. The method proposed in this study is useful in reducing the dependence on human experts and promoting the digitization of a forensic identification system based on palatal rugae.

Fractional Fourier Transform Based Adaptive Filtering Techniques for Acoustic Emission Signal Enhancement

Acoustic emission technique (AET) is a well-known non-destructive testing method used for the detection of crack growth and monitoring structural integrity of components. The main limitation in the application of AET is the fact that acoustic emission (AE) signal is often affected by background noise. A new approach is proposed in this paper to reduce the background noise and to improve the accuracy of AE signal detection. Various noise reduction methods have been applied and studied for AE signal enhancement so far. Some of the studies proved that self-adaptive noise cancellation (SANC) and adaptive noise cancellation (ANC) are better techniques for denoising the AE signal. This paper proposes the use of ANC and SANC schemes based on Fractional Fourier Transform (FrFT) for AE signal enhancement. FrFT is the generalization of the classical Fourier Transform (FT). The use of FrFT gives an advantage of an additional degree of freedom (angle of rotation in time–frequency plane) over the traditional Fourier transform and could provide improved performance. In this method, the noisy signal is rotated in time- frequency plane to extract the signal in Fractional Fourier domain (FrFD). Two adaptive filters viz. least mean squares and normalized least mean squares are studied for FrFD based ANC approach. The performance of the proposed method is validated using real AE signals acquired from three different experiments: pencil lead break test, composite drilling test and concrete compression test. Results are compared with the time and frequency domain adaptations. Moreover, the results have also been compared with the frequency domain adaptation techniques. Results have demonstrated that FrFD based ANC approach outperforms the conventional time domain and frequency domain adaptive filtering with an improved signal to noise ratio and significantly reduces mean square error.

A cryptosystem based on deterministic phase masks and fractional Fourier transform deploying singular value decomposition

In this paper, an asymmetric cryptosystem has been proposed to enhance the security of DRPE. The traditional DRPE scheme is thus tweaked by using fractional Fourier transform (FrFT), a class of structured phase masks called as deterministic phase masks (DMKs) and deploying singular value decomposition (SVD). In specific, we propose to organise the encryption procedure by using two DMKs and FrFT, additionally deploying SVD. On the decryption front, the input image is recovered by utilising the inverse singular value decomposition (ISVD) and an angular portion of the deterministic phase masks. The use of FrFT for encryption and decryption would enhance the robustness of DRPE scheme. Deployment of SVD on our asymmetric cryptosystem provides three components for cipher image is yet another added feature that hardens the security of DRPE scheme. DMKs are formed by the deviation from conventional rectangular function and limited range values which delivers key components with reduced size, better performance and lower complexity. The capability study of defined method, includes analysis on SVD, histogram and correlation coefficient. Our system is subject to an occlusion attack and noise attack to evaluate its performance and reliability. Computational analysis outputs and security investigation are offered in aspect to determine the security potential of proposed system. Comparative results are shown for values of mean-square-error and peak-signal-to-noise ratio of DRPE schemes.

Analyse Performance of Fractional Fourier Transform on Timing and Carrier Frequency Offsets Estimation

This paper deals with the performance of the use of fractional Fourier transform (FRFT) instead of conventional Fourier transform (FFT) in either symbol timing offset (STO) and carrier frequency offset (CFO) estimation. Orthogonal frequency division multiplexing is widely used in many systems due to advantages of theses technique compared with mono-carrier systems. In spite of his advantages, OFDM presents drawbacks such as sensitivity to timing and frequency offsets. Many techniques are used in the literature to estimate these two parameters in order to compensate them (synchronization task). These techniques used conventional Fourier transform. In this paper, we are interested in estimating STO and CFO using fractional Fourier transform. Monte Carlo simulation demonstrates the performance of the use of FRFT instead of FFT.