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The purpose of this paper is to study the existence and exponential stability of anti-periodic solutions of a class of shunting inhibitory cellular neural networks (SICNNs) with time-varying delays and continuously distributed delays.

The inequality technique and Lyapunov functional method are applied.

Sufficient conditions are obtained to ensure that all solutions of the networks converge exponentially to the anti-periodic solution, which are new and complement previously known results.

There are few papers that deal with the anti-periodic solutions of delayed SICNNs with the form negative feedback – a_ij(t)α_ij(x_ij(t)).

The purpose of this paper is to investigate the weighted pseudo-almost periodic solutions of shunting inhibitory cellular neural networks (SICNNs) with time-varying delays and distributed delays.

The principle of weighted pseudo-almost periodic functions and some new mathematical analysis skills are applied.

A set of sufficient criteria which guarantee the existence and exponential stability of the weighted pseudo-almost periodic solutions of the considered SICNNs are established.

The derived results of this paper are new and complement some earlier works. The innovation of this paper concludes two points: a new sufficient criteria guaranteeing the existence and exponential stability of the weighted pseudo-almost periodic solutions of SICNNs are established; and the ideas of this paper can be applied to investigate some other similar neural networks.

The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

The differential inequality theory and some novel mathematical analysis techniques are applied.

A set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.

It plays an important role in designing the neural networks.

The obtained results of this paper are new and complement some previous studies. The innovation of this paper concludes two aspects: the analysis on the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays is first proposed; and it is first time to establish the sufficient criterion which ensures the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

This study aims to analyze those factors affecting the rural resident’s willingness to adopt solar photovoltaic (PV) which is important for accelerating the popularization of clean energy in China.

This study contained a sample of 653 households in 8 provinces/regions by stratified, and random sampling in rural China. Descriptive analysis, exploratory factor analysis and confirmatory factor analysis techniques have been used for analytical purposes.

The empirical results indicate that financial incentive and social interaction have positive effects on rural residents’ adoption willingness, while village leaders’ engagement can indirectly influence their adoption willingness through social interaction and residents’ cognition.

This study mainly considers external and internal factors but ignores the effect of technical factors. In addition, the samples are just selected from the residents who have adopted solar PV.

This study is expected to be useful for the government, regulators, village leaders, village leaders and other institutions.

This study conducts a systematic analysis and clarifies the relationship between factors (external and internal) and rural residents’ adoption willingness. The village leaders’ engagement is first added to the conceptual model as an external factor, which is very essential in rural residents’ adoption in China.