Broadband Bioimpedance Spectroscopy Based on a Multifrequency Mixed Excitation and Nuttall Windowed FFT Algorithm

Bioimpedance spectroscopy (BIS) has become an important clinical indicator for monitoring the pathological status of biological tissues, and multifrequency simultaneous measurement of BIS may provide more accurate diagnostic information compared with the traditional frequency-sweep measurement technology. This paper proposes a BIS multifrequency simultaneous measurement method based on multifrequency mixed (MFM) signal excitation and a Nuttall windowed interpolation FFT algorithm. Firstly, the excitation source adopts the nine-frequency MFM signal f(9,t), which has excellent spectral characteristic and is very suitable for BIS measurement. On this basis, a Nuttall window is adopted to truncate sample data, and an interpolation FFT algorithm based on Nuttall window is built to perform spectral analysis, in which the parameter correction formula is provided based on polynomial approximation. A BIS measurement simulation experiment is performed on an RC three-element equivalent circuit, and results on the 9 primary harmonic frequencies ranging from 3.9 kHz to 1 MHz show a high accuracy with the impedance amplitude relative error |Ez|<0.3%, and the phase absolute error |Ep|<0.1°. This paper validates the feasibility of BIS multifrequency simultaneous measurement method and establishes an algorithm foundation for the development of practical broadband BIS measurement system

A Noise-Filtering Method for Link Prediction in Complex Networks.

Link prediction plays an important role in both finding missing links in networked systems and complementing our understanding of the evolution of networks. Much attention from the network science community are paid to figure out how to efficiently predict the missing/future links based on the observed topology. Real-world information always contain noise, which is also the case in an observed network. This problem is rarely considered in existing methods. In this paper, we treat the existence of observed links as known information. By filtering out noises in this information, the underlying regularity of the connection information is retrieved and then used to predict missing or future links. Experiments on various empirical networks show that our method performs noticeably better than baseline algorithms

A State Evaluation Adaptive Differential Evolution Algorithm for FIR Filter Design

Due to conventional differential evolution algorithm is often trapped in local optima and premature convergence in high dimensional optimization problems, a State Evaluation Adaptive Differential Evolution algorithm (SEADE) is proposed in this paper. By using independent scale factor on each dimension of optimization problem, and evaluating the distribution of population on each dimension, the SEADE correct the control parameters adaptively. External archive and a moving window evaluation mechanism on evolution state are introduced in SEADE to detect whether the evolution is stagnation or not, and with the help of opposition-based population, the algorithm can jump out of local optima basins. The results of experiments on several benchmarks show that the proposed algorithm is capable of improving the search performance of high dimensional optimization problems. And it is more efficient in design FIR digital filter using SEADE than conventional method like Parks-McClellan algorithm

Performance Comparison of Windowed Interpolation FFT and Quasisynchronous Sampling Algorithm for Frequency Estimation

The DFT-based frequency estimations have inherent limitations such as spectral leakage and picket-fence effect due to asynchronous sampling. This paper focuses on comparing the windowed interpolation FFT (WIFFT) and quasisynchronous sampling algorithm (QSSA) for frequency estimation. The WIFFT uses windows to reduce spectral leakage and employs interpolation algorithm to eliminate picket-fence effect. And the QSSA utilizes quasisynchronous weighted iterations for frequency estimation. The accuracy and time complexity of WIFFT and QSSA are theoretically studied. Computer simulations of frequency estimations with noise and fluctuations by using WIFFT and QSSA are performed. Simulations results show that the wideband noise sensitivity of QSSA is lower than that of WIFFT. However, the WIFFT exhibits less time complexity than QSSA

Demonstration of using rows of A + I as the feature vectors for nodes.

<p>In the network, nodes 4 and 5 are topologically equivalent. However, the 4th row of <b>A</b> reads [0, 1, 1, 0, 1], and the 5th reads [0, 1, 1, 1, 0], which are different. By adding <b>I</b>, the 4th and 5th rows of <b>A</b> + <b>I</b> now are both [0, 1, 1, 1, 1], which is exactly what we want. This is also the case for nodes 2 and 3. The <i>k</i>-th feature of a node can be interpreted as whether the distance between it and node <i>k</i> is no more than 1. For example, the distance between node 1 and 4 is greater than 1, while the distance between all the other nodes and node 4 are within 1, so the 4th feature is [0, 1, 1, 1, 1]^<i>T</i>.</p

Comparison of prediction accuracy under the precision metric.

<p>The fraction of training sets <i>f</i> is varied from 0.5 to 0.9.</p