This paper is concerned with the design and the synthesis of the impulsive positive observer (IPO) for positive linear continuous systems. The IPO can estimate the states for positive systems even when the measured ou...
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This paper addresses the multistability for a general class of recurrent neural networks with time-varying delays. Without assuming the linearity or monotonicity of the activation functions, several new sufficient con...
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This paper addresses the multistability for a general class of recurrent neural networks with time-varying delays. Without assuming the linearity or monotonicity of the activation functions, several new sufficient conditions are obtained to ensure the existence of (2K+1)(n) equilibrium points and the exponential stability of (K+1)(n) equilibrium points among them for n-neuron neural networks, where K is a positive integer and determined by the type of activation functions and the parameters of neural network jointly. The obtained results generalize and improve the earlier publications. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of these exponentially stable equilibrium points can be larger than their originally partitioned subsets. Finally, three illustrative numerical examples show the effectiveness of theoretical results.
Depth estimation is an important computer vision problem with many practical applications to mobile devices. While many solutions have been proposed for this task, they are usually very computationally expensive and t...
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An electroencephalogram (EEG) based brain-computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled individuals, e.g., amyotrophic lateral sc...
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In the application of neural interface, the neural activity of neurons and neuronal groups is not fixed even under the same task conditions. Meanwhile, the recording conditions of neural signals are also very unstable...
In the application of neural interface, the neural activity of neurons and neuronal groups is not fixed even under the same task conditions. Meanwhile, the recording conditions of neural signals are also very unstable, with a high degree of within-and across-day variability. This results in a very unstable firing pattern for the recorded neural spike signals. In order to get better performance, the decoder often requires a lot of online calibration samples. This brings a heavy training burden to neural interface users. To solve this problem, this paper proposes to apply transfer learning (TL) to online calibration of intracortical neural interface to reduce the dependence of decoder on a large number of online calibration samples. Experimental results show that through transferring from a large amount of historical data, decoder can achieve satisfactory classification accuracy with only a small amount of online data.
Based on the idea of 'q—count' of certain subwords of a word and generalizing the notion of Parikh matrix of a word, the notion of Parikh q—matrix of a word over an ordered alphabet was introduced. On the ot...
Based on the idea of 'q—count' of certain subwords of a word and generalizing the notion of Parikh matrix of a word, the notion of Parikh q—matrix of a word over an ordered alphabet was introduced. On the other hand, with a two-dimensional picture array of symbols arranged in rows and columns, two kinds of upper triangular matrices, known as row and column Parikh matrices have also been introduced and investigated. Here combining these two kinds of matrices of a picture array, we introduce row/column Parikh q—matrix of an array, leading to the concept of q—ambiguity of a picture array. Results relating to q—ambiguity of picture arrays are derived in the context of these Parikh q—matrices of arrays.
Shaoqing Wang1, Xiancun Yang2, Meixia Su1, Qiang Liu1 1Department of MRI, Shandong Medical Imaging Research Institute Affiliated to Shandong University, Jinan, Shandong, 250021, People's Republic of C...
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Shaoqing Wang1, Xiancun Yang2, Meixia Su1, Qiang Liu1 1Department of MRI, Shandong Medical Imaging Research Institute Affiliated to Shandong University, Jinan, Shandong, 250021, People's Republic of China; 2Department of Interventional Radiology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong, 250021, People's Republic of China Correspondence: Qiang Liu (2002md@***) Aims To evaluate the diagnostic value of three- dimensional rotational angiography (3D-RA) of intracranial micro-aneurysms (diameter ≤ 3 mm) and provide guidance on the value of endovascular treatment. Materials and methods 43 patients with intracranial micro-aneurysms were analyzed retrospectively, all patients had undergone angiography with both conventional 2D-DSA(Two-Dimensional Digital Subtraction Angiography) and rotational angiography with three-dimensional reconstruction; the frequency of detection of aneurysms, depiction of aneurysm neck, radiation dose, and the dosage of contrast agent were recorded respectively. Results 55 pieces of aneurysms were detected out from the 43 cases with intracranial micro-aneurysms by 3D-RA. But only 39 cases were detected out using 2D-DSA from the 55 samples, there were significant differences with regards to detection rate (P < 0.05). There were significant differences in radiation dose and dosage of contrast agent (P < 0.05) between the two methods of using 3D-RA can improve the detection rate of micro-aneurysms, which bestows obvious advantages on displaying the shape of aneurysms, the aneurysm neck at the best angle, and the relationship with the parent artery, at the same time, the amount of contrast agent and radiation dose are reduced in 3D-RA compared to 2D-DSA.
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