Simple Floating Voltage-Controlled Memductor Emulator for Analog Applications

The topic of memristive circuits is a novel topic in circuit theory that has become of great importance due to its unique behavior which is useful in different applications. But since there is a lack of memristor samples, a memristor emulator is used instead of a solid state memristor. In this paper, a new simple floating voltage-controlled memductor emulator is introduced which is implemented using commercial off the shelf (COTS) realization. The mathematical modeling of the proposed circuit is derived to match the theoretical model. The proposed circuit is tested experimentally using different excitation signals such as sinusoidal, square, and triangular waves showing an excellent matching with previously reported simulations

Power Dissipation of Memristor-Based Relaxation Oscillators

Recently, many reactance-less memristive relaxation oscillators were introduced, where the charging and discharging processes depend on memristors. In this paper, we investigate the power dissipation in different memristor based relaxation oscillators. General expressions for these memristive circuits as well as the power dissipation formulas for three different topologies are derived analytically. In addition, general expressions for the maximum and minimum power dissipation are calculated. Finally, the calculated expressions are verified using PSPICE simulations showing very good matching

Thermal Heating in ReRAM Crossbar Arrays: Challenges and Solutions

Increasing popularity of deep-learning-powered applications raises the issue of vulnerability of neural networks to adversarial attacks. In other words, hardly perceptible changes in input data lead to the output error in neural network hindering their utilization in applications that involve decisions with security risks. A number of previous works have already thoroughly evaluated the most commonly used configuration - Convolutional Neural Networks (CNNs) against different types of adversarial attacks. Moreover, recent works demonstrated transferability of the some adversarial examples across different neural network models. This paper studied robustness of the new emerging models such as SpinalNet-based neural networks and Compact Convolutional Transformers (CCT) on image classification problem of CIFAR-10 dataset. Each architecture was tested against four White-box attacks and three Black-box attacks. Unlike VGG and SpinalNet models, attention-based CCT configuration demonstrated large span between strong robustness and vulnerability to adversarial examples. Eventually, the study of transferability between VGG, VGG-inspired SpinalNet and pretrained CCT 7/3x1 models was conducted. It was shown that despite high effectiveness of the attack on the certain individual model, this does not guarantee the transferability to other models.Comment: 18 page

AudioFool: Fast, Universal and synchronization-free Cross-Domain Attack on Speech Recognition

Automatic Speech Recognition systems have been shown to be vulnerable to adversarial attacks that manipulate the command executed on the device. Recent research has focused on exploring methods to create such attacks, however, some issues relating to Over-The-Air (OTA) attacks have not been properly addressed. In our work, we examine the needed properties of robust attacks compatible with the OTA model, and we design a method of generating attacks with arbitrary such desired properties, namely the invariance to synchronization, and the robustness to filtering: this allows a Denial-of-Service (DoS) attack against ASR systems. We achieve these characteristics by constructing attacks in a modified frequency domain through an inverse Fourier transform. We evaluate our method on standard keyword classification tasks and analyze it in OTA, and we analyze the properties of the cross-domain attacks to explain the efficiency of the approach.Comment: 10 pages, 11 Figure

Thrust Enhancement and Degradation Mechanisms due to Self-Induced Vibrations in Bio-inspired Flying Robots

Whenever a flapping robot moves along a trajectory it experiences some vibration about its mean path. Even for a hovering case, a flier experiences such vibration due to the oscillatory nature of the aerodynamic forces. In this paper we have studied the effect of such vibration on hovering. We used two setups to measure thrust force generated by flapping robots. One involving loadcell, which does not allow any kind of vibration. The other one involves a pendulum which allows vibration at a particular direction. We used two different flapping robots; one is a traditional flapping robot with two wings and the other one is a four wings robot which exploits clap and peel mechanism to generate thrust. We observed that the loadcell setup measures more thrust for the two wings model than the pendulum setup. The opposite trend was observed for the four wings model. We measured the vibration induced velocity using motion capture system. We used well known aerodynamic models to observe the effect of the vibration during the flapping cycle. To gain physical insight into the vibration affected flow field, we used smoke flow visualization at different instances during the flapping cycle. It revealed that the perturbation ebbs a jet effect in case of the two wings which leads to its adverse effect for thrust generation. On the contrary the perturbation enhances the clapping effect for the four wings robot, resulting favorable for thrust generation