We develop a completely data-driven approach to reconstructing coupled neuronal networks that contain a small subset of chaotic neurons. Such chaotic elements can be the result of parameter shift in their individual dynamical systems and may lead to abnormal functions of the network. To accurately identify the chaotic neurons may thus be necessary and important, for example, applying appropriat...

We present an innovative approach to the synthesis of linear arrays having the least possible number of elements while radiating shaped beams lying in completely arbitrary power masks. The approach, based on theory and procedures lend from Compressive Sensing, has two innovative key features. First, it exploits at best the multiplicity of equivalent field solutions corresponding to the many dif...

The goal of sparse recovery is to recover a k-sparse signal x ∈ R from (possibly noisy) linear measurements of the form y = Ax, where A ∈ Rm×n describes the measurement process. Standard results in compressive sensing show that it is possible to recover the signal x from m = O(k log(n/k)) measurements, and that this bound is tight. The framework of modelbased compressive sensing [BCDH10] overco...

The application of compressive sensing and waveform design on the estimation of linear time-varying system characteristics using noisy measurements is investigated in this paper. Due to the sparsity of the system’s spreading function representation and the inherent noise in any real-world sensor or measurement device, we propose a new method based on our previous work for identifying narrowband...

— A compressive sensing (CS) reconstruction method for polynomial phase signals is proposed in this paper. It relies on the Polynomial Fourier transform, which is used to establish a relationship between the observation and sparsity domain. Polynomial phase signals are not sparse in commonly used domains such as Fourier or wavelet domain. Therefore, for polynomial phase signals standard CS algo...

Accurate moisture sensing is an important need for many research programs as well as in control of industrial processes. This paper describes the development of a high accuracy frequency domain sensing probe for use in obtaining dielectric measurements of materials suitable for work ranging from 300 MHz to 1 GHz. The probe was developed to accommodate a wide range of permittivity’s ranging from...

We study the problem of recursively reconstructing a time sequence of sparse vectors St from measurements of the form Mt = ASt+BLt where A and B are known measurement matrices, and Lt lies in a slowly changing low dimensional subspace. We assume that the signal of interest (St) is sparse, and has support which is correlated over time. We introduce a solution which we call Recursive Projected Mo...

The performance of cooperative spectrum sensing in cognitive radio (CR) networks depends on the sensing mode, the sensing time and the number of cooperative users. In order to improve the sensing performance and reduce the interference to the primary user (PU), a periodic cooperative spectrum sensing model based on weight fusion is proposed in this paper. Moreover, the sensing period, the sensi...

in this work we introduce a practical use of synthesized schiff base metal complex in sensing application. a new perchlorate-selective electrode based on the complex n, n'-4-nitro-phenylmethanebis-(salicylaldiminato) copper (ii) [cul] as the membrane carrier was developed. the electrode exhibits a good  nernstian slope of -55.0 ± 1.0 mv/decade and a linear range of  for perchlorate. the limit o...