A Method of Trend Extraction Using Singular Spectrum Analysis
نویسنده
چکیده
• The paper presents a new method of trend extraction in the framework of the Singular Spectrum Analysis (SSA) approach. This method is easy to use, does not need specification of models of time series and trend, allows to extract trend in the presence of noise and oscillations and has only two parameters (besides basic SSA parameter called window length). One parameter manages scale of the extracted trend and another is a method specific threshold value. We propose procedures for the choice of the parameters. The presented method is evaluated on a simulated time series with a polynomial trend and an oscillating component with unknown period and on the seasonally adjusted monthly data of unemployment level in Alaska for the period 1976/01– 2006/09. Key-Words: • time series; trend extraction; Singular Spectrum Analysis. AMS Subject Classification: • 37M10, 15A18, 60G35, 62M15. 2 Theodore Alexandrov A Method of Trend Extraction Using SSA 3
منابع مشابه
Predicting the Brexit outcome using singular spectrum analysis
In a referendum conducted in the United Kingdom (UK) on June 23, 2016, $51.6\%$ of the participants voted to leave the European Union (EU). The outcome of this referendum had major policy and financial impact for both UK and EU, and was seen as a surprise because the predictions consistently indicate that the ``Remain'''' would get a majority. In this paper, we investigate whether the outcome o...
متن کاملNoise Effects on Modal Parameters Extraction of Horizontal Tailplane by Singular Value Decomposition Method Based on Output Only Modal Analysis
According to the great importance of safety in aerospace industries, identification of dynamic parameters of related equipment by experimental tests in operating conditions has been in focus. Due to the existence of noise sources in these conditions the probability of fault occurrence may increases. This study investigates the effects of noise in the process of modal parameters identification b...
متن کاملA Unique Approach of Noise Elimination from Electroencephalography Signals between Normal and Meditation State
In this paper, unique approach is presented for the electroencephalography (EEG) signals analysis. This is based on Eigen values distribution of a matrix which is called as scaled Hankel matrix. This gives us a way to find out the number of Eigen values essential for noise reduction and extraction of signal in singular spectrum analysis. This paper gives us an approach to classify the EEG signa...
متن کاملA Time-Frequency approach for EEG signal segmentation
The record of human brain neural activities, namely electroencephalogram (EEG), is generally known as a non-stationary and nonlinear signal. In many applications, it is useful to divide the EEGs into segments within which the signals can be considered stationary. Combination of empirical mode decomposition (EMD) and Hilbert transform, called Hilbert-Huang transform (HHT), is a new and powerful ...
متن کاملDisguised Face Recognition by Using Local Phase Quantization and Singular Value Decomposition
Disguised face recognition is a major challenge in the field of face recognition which has been taken less attention. Therefore, in this paper a disguised face recognition algorithm based on Local Phase Quantization (LPQ) method and Singular Value Decomposition (SVD) is presented which deals with two main challenges. The first challenge is when an individual intentionally alters the appearance ...
متن کامل