17 Detecting beef eating quality in a non-destructive way has been popular in recent years. 18 Among various non-destructive assessing methods, the feasibility of hyperspectral imaging 19 (HSI) system was investigated in this paper. Hyperspectral images of beef samples were 20 collected in an abattoir production line and used for predicting the beef tenderness and pH 21 value. Support vector ma...

The Singular Spectrum Analysis (SSA)-Autoregressive Integrated Moving Average (ARIMA) hybrid method is a good combination of forecasting methods to improve accuracy and suitable for economic data that tends have trend seasonal patterns, one which inflation data. purpose this study obtain the results East Kalimantan Province in 2021 using SSA-ARIMA model. SSA-ARIMA(1,1,1) model overall experienc...

In this paper, we develop a new extension of the singular spectrum analysis (SSA) called functional SSA to analyze time series. The methodology is constructed by integrating ideas from data and univariate SSA. Specifically, introduce trajectory operator in world, which equivalent matrix regular SSA, one needs obtain value decomposition (SVD) decompose given Since there no procedure extract SVD ...

Seasonal signals (annual plus semi-annual) in GPS time series are of great importance for understanding the evolution of regional mass, i.e. ice and hydrology. Conventionally these signals (annual and semi-annual) are derived by least-squares fitting of harmonic terms with a constant amplitude and phase. In reality, however, such seasonal signals are modulated, i.e. they will have a time-variab...

Singular spectrum analysis (SSA), a linear (univariate and multivariate) time series technique , performs principal component analysis (PCA) on an augmented dataset containing the original data and time-lagged copies of the data. Neural network theory has meanwhile allowed PCA to be generalized to nonlinear PCA (NLPCA). In this paper, NLPCA is further extended to perform nonlinear SSA (NLSSA): ...

Both the heart sound and lung sound are produced within the almost same region of the human body. Heart sound makes severe interference while hearing the lung sound for the diagnosis purpose. So the separation of these sounds is very important for a accurate diagnosis. A special Advanced Line Enhancer (ALE), employing the strength of Singular Spectrum Analysis (SSA) is used in this paper. The S...

Singular spectrum analysis (SSA), a linear univariate and multivariate time series technique , is essentially principal component analysis (PCA) applied to the time series and additional copies of the time series lagged by 1 to K time steps. Neural network theory has meanwhile allowed PCA to be generalized to nonlinear PCA (NLPCA). In this paper, NLPCA is further extended to perform nonlinear S...