In this paper, a Hopfield‐type neural network system with Caputo–Hadamard fractional derivative is discussed. The importance of the existence of the equilibrium point in the analysis of artificial neural networks is well known. Another important investigation is the stability properties. So, the stability of a neural network system is dealt with in the present paper. First, a theorem that asserts the existence and uniqueness of the equilibrium point of the system is proven. Later, the conditions that ensure the Mittag‐Leffler stability of the equilibrium point is obtained by using the Lyapunov's direct method. In addition, an example is given with numerical simulations to show the effectiveness of our theoretical results.

Consider the first-order linear differential equation with several non-monotone retarded arguments x ′ ⁢ ( t ) + ∑ i = 1 m p i ⁢ ( t ) ⁢ x ⁢ ( τ i ⁢ ( t ) ) = 0 {x^{\prime}(t)+\sum_{i=1}^{m}p_{i}(t)x(\tau_{i}(t))=0} , t ≥ t 0 {t\geq t_{0}} , where the functions p i , τ i ∈ C ⁢ ( [ t 0 , ∞ ) , ℝ + ) {p_{i},\tau_{i}\in C([t_{0},\infty),\mathbb{R}^{+})} , for every i = 1 , 2 , … , m {i=1,2,\ldots,m} , τ i ⁢ ( t ) ≤ t {\tau_{i}(t)\leq t} for t ≥ t 0 {t\geq t_{0}} and lim t → ∞ ⁡ τ i ⁢ ( t ) = ∞ {\lim_{t\to\infty}\tau_{i}(t)=\infty} . New oscillation criteria which essentially improve the known results in the literature are established. An example illustrating the results is given.

We prove the existence and uniqueness of solutions of a class of second order differential equations with piecewise constant mixed arguments and we show that the zero solution of Eq. (1.1) is a global attractor. Also, we study some properties of solutions of Eq. (1.1) such as oscillation, nonoscillation, and periodicity.

This paper concerns with the existence of the solutions of a second order impulsive delay differential equation with a piecewise constant argument. Moreover, oscillation, nonoscillation and periodicity of the solutions are investigated.