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Published in Philip A. Laplante, Comprehensive Dictionary of Electrical Engineering, 2018
biomass General term used for wood, wood wastes, sewage, cultivated herbaceous and other energy crops, and animal wastes. biomedical sensor a device for interfacing an instrumentation system with a biological system such as biological specimen or an entire organism. The device serves the function of detecting and measuring in a quantitative fashion a physiological property of the biological system. biometric verifier device that helps authenticate by measuring human characteristics. biorthogonal filter bank a filter bank that satisfies the perfect reconstruction condition, i.e., the product of the polyphase transfer function of the analysis and synthesis filters is a pure delay. In general, the analysis and synthesis filters are different, as opposed to the situation for an orthogonal filter bank. biorthogonal wavelet a generalization of orthogonal wavelet bases, where two dual basis functions span two sets of scaling spaces, V j and ^ ^ V j , and two sets of wavelet spaces, W j and W j , with each scaling space orthogonal to the dual ^ ^ wavelet space, i.e. V j W j and V j W j where "" represents "orthogonal to." See biorthogonal filter bank. BIOS See basic input-output system.
Transform Domain Speech Processing
Published in Shaila Dinkar Apte, Random Signal Processing, 2017
We considered one representative of orthogonal wavelets, namely, Daubechies wavelet. It was indicated that the wavelet and scaling functions are not symmetrical or are antisymmetrical. Matrix multiplication method for computation of wavelet decomposition is explained. The properties of orthogonal wavelet family are discussed. We calculated the number of operations and time bandwidth product. Other wavelets such as spline, Mexican hat, and Gaussian basis are introduced. We also considered biorthogonal wavelet basis and its properties. We introduced spline biorthogonal wavelets and wavelet packets.
Covid-19 diagnosis by WE-SAJ
Published in Systems Science & Control Engineering, 2022
Wei Wang, Xin Zhang, Shui-Hua Wang, Yu-Dong Zhang
However, most of the research on Shannon's entropy has been on engineering applications, and its physical meaning and principles have not been discussed in depth. Moreover, the shortcomings of Shannon entropy make it prone to wavelet mixing and energy leakage when dealing with non-stationary signals, which may lead to inaccurate or even incorrect results. Given this, many new solutions to these problems have emerged, such as relative wavelet entropy (Rosso et al., 2001) and Tsallis Wavelet Entropy (Chen & Li, 2014). Our research uses a 4-level decomposition of biorthogonal wavelets. Compared to orthogonal wavelet bases, biorthogonal wavelet bases resolve the incompatibility of symmetry and exact signal reconstruction. Biorthogonal wavelets consist of two wavelets called dyads, which decompose and reconstruct the signal separately. Bi-orthogonal wavelets resolve the contradiction between linear phase and orthogonality requirements and are widely used in signal and image reconstruction. In this research, wavelet entropy is used for feature extraction. And then, the extracted features are fed into a two-layer Feedforward Neural Network for classification.
Colour filter array demosaicking over compression through modified grey wolf optimization technique
Published in The Imaging Science Journal, 2018
M. S. Safna Asiq, W. R. Sam Emmanuel
The proposed work has a lossless compression technique with biorthogonal wavelet transform. A single scaling function is replaced by two scaling functions in biorthogonal wavelet transform. The energy is concentrated on only a few of the coefficients. Biorthogonal wavelet provides more degree of freedom than other orthonormal transforms. The approximation values are in a minimum range and the details of the image are preserved in order to retain the details of the image. Figure 4 depicts the vertical, diagonal and horizontal coefficient details of the image on applying the biorthogonal wavelet transform for image compression. The huge amount of coefficients are made zero for the compression to be efficient. An essential amount of zero helps in the lossless compression; about 43% of the coefficients are converted to zero for compression. The coefficients are optimized using MGWO.
Generation of enhanced information image using curvelet-transform-based image fusion for improving situation awareness of observer during surveillance
Published in International Journal of Image and Data Fusion, 2019
Wavelet-transform-based technique is a form of multi-resolution transform in which the image is decomposed using filter banks to extract coarse and detailed coefficients of an image at every level. These extracted coefficients are then fused using specific fusion rules. The fused coefficients are then rearranged to form a matrix as per their level and fused image is reconstructed using another reconstruction filter bank. The orthogonal wavelet technique makes use of same filter bank for decomposition and reconstruction. However, biorthogonal wavelet families use separate decomposition and reconstruction filters.