Model transformasi wavelet diskrit dengan dekomposisi nilai singular pada wavelet haar - Utami, Defita Rani; Saputro, Dewi Retno Sari (Prosiding Seminar Nasional Matematika dan Pendidikan Matematika, 2021)
A wavelet is a transformation function that automatically cuts data into different components and studies each component with a resolution appropriate to its scale. The wavelet model is used for nonparametric data analysis, density estimation, point of change problems, and special aspects of time series. One of the wavelet models is the Haar wavelet transform model. The purpose of this research is to study the Haar wavelet model which is performed using Discrete Wavelet Transform (DWT) combined with Single Value Decomposition (SVD) to produce subsignals. Discrete Wavelet Transform (DWT) is a signal transformation that combines time and frequency. Haar wavelet transform is determined using Discrete Wavelet Transform (DWT) with discrete Fourier transform to describe the signal. In decomposing the signal into two sub-signals, it can be done with Single Value Decomposition (SVD) by using matrix calculations. The result of this research is Haar wavelet model construction with wavelet transform to determine the wavelet function using Discrete Wavelet Transform (DWT) and Single Value Decomposition (SVD).