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Abstract and Applied Analysis
Volume 2013 (2013), Article ID 463076, 7 pages
Global Exponential Stability of Positive Pseudo-Almost-Periodic Solutions for a Model of Hematopoiesis
College of Mathematics, Physics and Information Engineering, Jiaxing University, Jiaxing, Zhejiang 314001, China
Received 11 August 2013; Accepted 16 October 2013
Academic Editor: Chuanzhi Bai
Copyright © 2013 Junxia Meng. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citations to this Article [7 citations]
The following is the list of published articles that have cited the current article.
- Bingwen Liu, “New results on the positive almost periodic solutions for a model of hematopoiesis,” Nonlinear Analysis: Real World Applications, vol. 17, pp. 252–264, 2014.
- Lian Duan, and Lihong Huang, “Pseudo almost periodic dynamics of delay Nicholson's blowflies model with a linear harvesting term,” Mathematical Methods in the Applied Sciences, 2014.
- Wei Chen, and Wentao Wang, “Global Exponential Stability of Positive Almost Periodic Solutions for a Delay Logarithmic Population Model,” Journal of Applied Mathematics, vol. 2014, pp. 1–6, 2014.
- Wentao Wang, and Bingwen Liu, “Global Exponential Stability of Pseudo Almost Periodic Solutions for SICNNs with Time-Varying Leakage Delays,” Abstract and Applied Analysis, vol. 2014, pp. 1–17, 2014.
- Hong Zhang, Shuhua Gong, and Jianying Shao, “Global Exponential Stability of Positive Almost Periodic Solutions for a Fishing Model with a Time-Varying Delay,” Abstract and Applied Analysis, vol. 2014, pp. 1–11, 2014.
- Changjin Xu, Qiming Zhang, and Yusen Wu, “Existence and stability of pseudo almost periodic solutions for shunting inhibitory cellular neural networks with neutral type delays and time-varying leakage delays,” Network-Computation in Neural Systems, vol. 25, no. 4, pp. 168–192, 2014.
- Bingwen Liu, “Pseudo Almost Periodic Solutions for CNNs with Continuously Distributed Leakage Delays,” Neural Processing Letters, vol. 42, no. 1, pp. 233–256, 2015.