Glial cells include several types of cells such as astrocytes, and oligodendrocytes apart from the neurons in the brain. In particular, astrocytes are known to be important in higher brain function and are therefore sometimes simply called glial cells. An astrocyte can transmit signals to other astrocytes and neurons using ion concentrations. Thus, we expect that the functions of an astrocyte can be applied to an artificial neural network. In this study, we propose a multi-layer perceptron (MLP) with a pulse glial chain. The proposed MLP contains glia (astrocytes) in a hidden layer. The glia are connected to neurons and are excited by the outputs of the neurons. The excited glia generate pulses that affect the excitation thresholds of the neurons and their neighboring glia. The glial network provides a type of positional relationship between the neurons in the hidden layer, which can enhance the performance of MLP learning. We confirm through computer simulations that the proposed MLP has better learning performance than a conventional MLP.

In this study, we propose a multi-layer perceptron with a glial network which is inspired from the features of glias in the brain. All glias in the proposed network generate independent oscillations, and the oscillations propagate through the glial network with attenuation. We apply the proposed network to the two-spiral problem. Computer simulations show that the proposed network gains a better performance than the conventional multi-layer perceptron.

We propose a new analysis technique against a class of countermeasure using randomized binary signed digit (BSD) representations. We also introduce some invariant properties between BSD representations. The proposed analysis technique can directly recover the secret key from power measurements without information for algorithm because of the invariant properties of BSD representation. Thus the proposed attack is applicable to all countermeasures using BSD representations. Finally, we give the simulation results against some countermeasures using BSD representation such as Ha-Moon method, Ebeid-Hasan method, and the method of Agagliate et al. The results show that the proposed attack is practical analysis method.