This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...

We present an efficient method for the reduction of model equations in the linearized diffuse optical tomography (DOT) problem. We first implement the maximum a posteriori (MAP) estimator and Tikhonov regularization, which are based on applying preconditioners to linear perturbation equations. For model reduction, the precondition is split into two parts: the principal components are consid...

nowdays,  iron  nanoparticles  due  to  their  unique  characteristics  are used  in  all  of  sciences  and  technology.  these  nano  particles  due  to their  electrical, magnetic,  optical  and  catalytic  properties  and  having high  area  and  activity  that  is  promped  by  their  small  size  and most importantly  many  scientists  from  the  entire  world  are  interested  in their  ...

energy crisis, global warming and other environmental issues are what motivate researchers to find new strategies to reduce energy consumption in buildings. recently, using phase change materials (pcm) in the building’s envelopes has drawn significant attention as an energy-saving method, which helps in increasing the building’s thermal capacity. in the present research, the effects of the main...