The problem of restoring an analog signal from its sampled measurements is called the signal reconstruction problem. A reconstructor is said to be consistent if the resampling of the reconstructed signal by the acquisition system would produce exactly the same measurements. The consistency requirement is frequently used in signal processing applications as the design criterion for signal recons...

The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owin...

This paper presents a new method for signal reconstruction by leveraging sampled-data control theory. We formulate the signal reconstruction problem in terms of an analog performance optimization problem using a stable discrete-time filter. The proposed H∞ performance criterion naturally takes intersample behavior into account, reflecting the energy distributions of the signal. We present metho...

Introduction:In this study, ECG signals have been embedded into medical images to create a novel blind watermarking method. The embedding is done when the original image is compressed using the EZW algorithm. The extraction process is performed at the decompression time of the watermarked image. Materials and Methods: The multi-resolution watermarking with a secret key algorithm developed in th...

introduction:in this study, ecg signals have been embedded into medical images to create a novel blind watermarking method. the embedding is done when the original image is compressed using the ezw algorithm. the extraction process is performed at the decompression time of the watermarked image. materials and methods: the multi-resolution watermarking with a secret key algorithm developed in th...

The aim of this work is to propose a method based on B-splines for signal filtering and signal reconstruction. The proposed approach consists of applying the Moore-Penrose inverse for the reconstruction of noisy signals and the use of smoothing techniques with a Whittaker smoother to control the roughness of variation in order to extract the signal from a noisy series. The advantages of this me...

Discrete time signal is nothing but samples continuous time signal and this process is called as sampling. If inter-sampling distance is constant it is called as uniform sampling and if distance is unequal, it is non-uniform sampling. Irrespective of type of sampling, reconstruction is possible if sampling rate do not exceed Nyquist rate. Sinc interpolation is one of the methods which results i...

This paper presents a new method for signal reconstruction by leveraging sampled-data control theory. We formulate the signal reconstruction problem in terms of an analog performance optimization problem using a stable discretetime filter. The performance criterion naturally takes intersample behavior into account. We present methods for computing optimal solutions which are guranteed to be sta...

Traditionally image reconstruction is done by performing Fast Fourier Transform (FFT). But recently there has been growing interest in using compressive sensing (CS) to perform image reconstruction.In compressive sensing, the main property of signal-Sparsity is explored for reconstruction purposes.In this paper, for image reconstruction, various optimization techniques like L1 optimization, Tot...

In this paper, we consider the topic of iterative, one dimensional, signal reconstruction (specifically speech signals) from the magnitude spectrum and the phase spectrum. While this topic has been extensively researched and documented, we wish to recast some well-established results for the benefit of new researchers and those who desire a short, yet comprehensive, review of the subject. The t...