in this paper robust pid control of fully-constrained cable driven parallel manipulators with elastic cables is studied in detail. in dynamic analysis, it is assumed that the dominant dynamics of cable can be approximated by linear axial spring. to develop the idea of control for cable robots with elastic cables, a robust pid control for cable driven robots with ideal rigid cables is firstly de...

The neural network-based nonlinear singular spectrum analysis (NLSSA) is applied to the zonal winds in the 70-10 hPa region (roughly 20-30 km altitude) measured at near-equatorial stations during 1956-2000. The data are pre-filtered by the linear singular spectrum analysis (SSA), with the leading 8 SSA principal components (PCs) used as inputs for the NLSSA. The NLSSA fits a curve to the data i...

Cognitive radio networks (CRNs) is a promising technology that allows secondary users (SUs) extensively explore spectrum resource usage efficiency, while not introducing interference to licensed users. Due to the unregulated wireless network environment, CRNs are susceptible to various malicious entities. Thus, it is critical to detect anomalies in the first place. However, from the perspective...

An automatic Singular Spectrum Analysis based methodology is proposed to decompose and reconstruct time-series. We suggest a clustering based procedure to identify the main dynamics of the input signal, by computing a subset of orthogonal basis using a power spectrum criterion. The subset of basis are represented by the Discrete Fourier Transform to infer basis vectors encoding similar data str...

This paper proposes a blind, inaudible, robust digitalaudio watermarking scheme based on singular-spectrum analysis, which relates to watermarking techniques based on singular value decomposition. We decompose a host signal into its oscillatory components and modify amplitudes of some of those components with respect to a watermark bit and embedding rule. To improve the sound quality of a water...

In recent years Singular Spectrum Analysis (SSA), used as a powerful technique in time series analysis, has been developed and applied to many practical problems. In this paper, we introduce the SSA technique based on the minimum variance estimator. We also consider the SSA technique based on the minimum variance and structured total least squares estimators in reconstructing and forecasting ti...

Singular spectrum analysis has recently become an attractive tool in a broad range of applications. Its main mechanism of alternating between rank reduction and Hankel projection to produce an approximation to a particular component of the original time series, however, deserves further mathematical justification. One paramount question to ask is how good an approximation that such a straightfo...

New filtering and spectral interpretations of Singular Spectrum Analysis (SSA) are provided. It is shown that the variables reconstructed from diagonal averaging of reduced-rank approximations to the trajectory matrix can be obtained from a noncausal convolution filter with zero-phase characteristics. The reconstructed variables are readily constructed using a two-pass filtering algorithm that ...

[1] Observational data sets in space physics often contain instrumental and sampling errors, as well as large gaps. This is both an obstacle and an incentive for research, since continuous data sets are typically needed for model formulation and validation. For example, the latest global empirical models of Earth’s magnetic field are crucial for many space weather applications, and require time...

Drosophila segmentation as a model organism is one of the most highly studied. Among many maternal segmentation coordinate genes, bicoid protein pattern plays a significant role during Drosophila embryogenesis, since this gradient determines most aspects of head and thorax development. Despite the fact that several models have been proposed to describe the bicoid gradient, due to its associatio...