Spatiotemporal observations in Earth System sciences are often affected by numerous and/or systematically distributed gaps. This data fragmentation is inherited from instrument failures, sparse measurement protocols, or unfavourable conditions (e.g. clouds or vegetation thickness in case of remote-sensing data). Missing values are problematic as they may cause analytic biases and often inhibit ...

A constructive methodology for shaping a neural model of a non-linear process, supported by results and prescriptions related to the Takens-Mañé theorem, has been recently proposed. Following this approach, the measurement of the first minimum of the mutual information of the output signal and the estimation of the embedding dimension using the method of global false nearest neighbors permit to...

Recently, the rapid development of deep learning has greatly improved performance image classification. However, a central problem in hyperspectral (HSI) classification is spectral uncertainty, where features alone cannot accurately and robustly identify pixel point image. This paper presents novel HSI network called MS-RPNet, i.e., multiscale superpixelwise RPNet, which combines superpixel-bas...

* Permanent address: Space Science Department, Rutherford Appleton Laboratory, Chilton, Didcot, OX11 0QX, UK and Department of Physics, University of Oxford, UK (e-mail: m.allen16physics.oxford.ac.uk) Abstract. Extended empirical orthogonal functions (EEOFs), alternatively known as multi-channel singular systems (or singular spectrum) analysis (MSSA), provide a natural method of extracting osci...

In this paper, the data analysis and short term price forecasting in Iran electricity market as a market with pay-as-bid payment mechanism has been considered. The proposed method is a modified singular spectral analysis (SSA) method. SSA decomposes a time series into its principal components i.e. its trend and oscillation components, which are then used for time series forecasting effectively....

Understanding and measuring financial cycles is important to academics policy-makers, particularly those in charge of macroprudential policy. While business cycle periodic components have been largely estimated with different methods, empirical evidence related cycles’ periodicities scarce. Worse, ad hoc filters, are commonly used by policy-makers calculate the credit gap make policy decisions ...

Novel coronavirus (COVID-19) was discovered in Wuhan, China December 2019, and has affected millions of lives worldwide. On 29th April 2020, Malaysia reported more than 5,000 COVID-19 cases; the second highest Southeast Asian region after Singapore. Recently, a forecasting model developed to measure predict cases on daily basis for next 10 days using previously-confirmed cases. A Recurrent Fore...

Former watermarking techniques have been largely developed for natural videos. Important applications including virtual reality, computer games, cartoons and movies involve another category of visual data, the computer animation. In this paper, we develop robust watermarking techniques to protect MPEG-4 2D mesh animation against copyright infringement. Three time-series analysis tools, the disc...

The Spectrum Sliding Analysis (SSA) is a dynamic spectrum analysis in which the next analysis interval differs from the previous one by including the next signal sample and excluding the first one from the previous analysis interval. Such a spectrum analysis is necessary for time-frequency localization of analyzed signals with given peculiarities. Using the well-known Fast Fourier Transform (FF...