This research paper presents the wireless data and power transfer system for optogenetics visual cortical prosthesis. The system uses the inductive coupling power transfer and 2.4GHz Bluetooth 4.0 data transfer. This system contains two hardware parts: the external headset consists of power and data transmitters, image capture, and image processing units; the subcutaneous implant PCB consists of power and data receiver and the control unit. We also present the relative image processing method for this system. The whole system could power and control the optogenetic neural stimulus of the

Steady State Visually Evoked Potentials (SSVEPs) are intrinsic responses to specific visual stimulus frequencies. When the retina is activated by a frequency ranging from 3.5 to 75 Hz, the brain produces electrical activity at the same frequency as the visual signal, or its multiples. Identifying the preferred frequencies of neurocortical dynamic processes is a benefit of SSVEPs. However, the time consumed during calibration sessions limits the number of training trials and gives rise to visual fatigue since there is significant human variation across and within individuals over time, which

Diabetes is a chronic condition that is characterized by high blood glucose levels and can cause damage to multiple organs over time. Continuous monitoring of glucose levels is essential for both diabetic and non-diabetic individuals. There have been major developments in glucose monitoring technology over the past decade, which have been driven by research and industry efforts. Despite these significant advancements, the area of glucose biosensors still faces significant challenges. This paper presents a comprehensive summary of the latest glucose monitoring technologies, including invasive

This paper presents an improved memristor-based relaxation oscillator which offers higher frequency and wider tunning range than the existing reactance-less oscillators. It also has the capability of operating on two positive supplies or alternatively a positive and negative supply. Furthermore, it has the advantage that it can be fully integrated on-chip providing an area-efficient solution. On the other hand, The oscillation concept is discussed then a complete mathematical analysis of the proposed oscillator is introduced. Furthermore, the power consumption of the new relaxation circuit is

This paper presents a comparative study of edge detection algorithms based on integer and fractional order differentiation. A performance comparison of the two algorithms has been proposed. Then, a soft computing technique has been applied to both algorithms for better edge detection. From the simulations, it shows that better performance is obtained compared to the classical approach. The noise performances of those algorithms are analyzed upon the addition of random Gaussian noise, as well as the addition of salt and pepper noise. The performance has been compared to peak signal to noise

The discrete logistic map is one of the most famous discrete chaotic maps which has widely spread applications. This paper investigates a set of four generalized logistic maps where the conventional map is a special case. The proposed maps have extra degrees of freedom which provide different chaotic characteristics and increase the design flexibility required for many applications such as quantitative financial modeling. Based on the maximum chaotic range of the output, the proposed maps can be classified as positive logistic map, mostly positive logistic map, negative logistic map, and

This paper presents a generalization of chaotic systems using two-dimensional affine transformations with six introduced parameters to achieve scaling, reflection, rotation, translation and/or shearing. Hence, the location of the strange attractor in space can be controlled without changing its chaotic dynamics. In addition, the embedded parameters enhance the randomness and sensitivity of the system and control its response. This approach overpasses performing the transformations as post-processing stages by applying them on the resulting time series. Trajectory control through dynamic

In this paper, we present new approaches to study the co-existence of some types of synchronisation between hyperchaotic dynamical systems. The paper first analyses, based on stability theory of linear continuous-Time systems, the co-existence of the projective synchronisation (PS), the function projective synchronisation (FPS), the full state hybrid function projective synchronisation (FSHFPS) and the generalised synchronisation (GS) between general master and slave hyperchaotic systems. Successively, using Lyapunov stability theory, the coexistence of three different synchronisation types is

Convolutional Neural Networks (CNNs) for Artificial Intelligence (AI) algorithms have been widely used in many applications especially for image recognition. However, the growth in CNN-based image recognition applications raised challenge in executing millions of Multiply and Accumulate (MAC) operations in the state-of-The-Art CNNs. Therefore, GPUs, FPGAs, and ASICs are the feasible solutions for balancing processing speed and power consumption. In this paper, we propose an efficient hardware architecture for CNN that provides high speed, low power, and small area targeting ASIC implementation

Binary convolutional neural networks (BCNN) have been proposed in the literature for resource-constrained IoTs nodes and mobile computing devices. Such computing platforms have strict constraints on the power budget, system performance, processing and memory capabilities. Nonetheless, the platforms are still required to efficiently perform classification and matching tasks needed in various applications. The memristor device has shown promising results when utilized for in-memory computing architectures, due to its ability to perform storage and computation using the same physical element