Modern digital integrated circuits (ICs) are often designed and fabricated by third parties and tools, which can make IC design/fabrication vulnerable to malicious modifications. The malicious circuits are generally referred to as hardware Trojans (HTs) and they are considered to be a serious security concern. In this paper, we propose a logic-testing based HT detection and classification method utilizing steady state learning. We first observe that HTs are hidden while applying random test patterns in a short time but most of them can be activated in a very long-term random circuit operation. Hence it is very natural that we learn steady signal-transition states of every suspicious Trojan net in a netlist by performing short-term random simulation. After that, we simulate or emulate the netlist in a very long time by giving random test patterns and obtain a set of signal-transition states. By discovering correlation between them, our method detects HTs and finds out its behavior. HTs sometimes do not affect primary outputs but just leak information over side channels. Our method can be successfully applied to those types of HTs. Experimental results demonstrate that our method can successfully identify all the real Trojan nets to be Trojan nets and all the normal nets to be normal nets, while other existing logic-testing HT detection methods cannot detect some of them. Moreover, our method can successfully detect HTs even if they are not really activated during long-term random simulation. Our method also correctly guesses the HT behavior utilizing signal transition learning.

This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.

In this paper, we propose a simple nonlinear system which consists of a chaotic spiking oscillator and a controlling circuit to stabilize unknown periodic orbits. Our proposed system generates various stabilized unknown Unstable Periodic Orbits which are embedded on the chaotic attractor of the original chaotic spiking oscillator. The proposed system is simple and exhibits various bifurcation phenomena. The dynamics of the system is governed by 1-D piecewise linear return map. Therefore, the rigorous analysis can be performed. We provide conditions for stability and almost complete analysis for bifurcation and co-existence phenomena by using the 1-D return map. An implementation example of the controlled chaotic spiking oscillator is provided to confirm some theoretical results.

For execution of computation-intensive applications, one of the most important paradigms is to divide the application into a large number of small independent tasks and execute them on heterogeneous parallel computing environments (abbreviated by HPCEs). In this paper, we aim to execute independent tasks efficiently on HPCEs. We consider the problem to find a schedule that maximizes the throughput of task execution for a huge number of independent tasks. First, for HPCEs where the network forms a directed acyclic graph, we show that we can find, in polynomial time, a schedule that attains the optimal throughput. Secondly, for arbitrary HPCEs, we propose an (+ε)-approximation algorithm for any constant ε(ε>0). In addition, we also show that the framework of our approximation algorithm can be applied to other collective communications such as the gather operation.

In this paper, we consider the steady state mean square error (MSE) analysis for 2-D LMS adaptive filtering algorithm in which the filter's weights are updated along both vertical and horizontal directions as a doubly-indexed dynamical system. The MSE analysis is conducted using the well-known independence assumption. First we show that computation of the weight-error covariance matrix for doubly-indexed 2-D LMS algorithm requires an approximation for the weight-error correlation coefficients at large spatial lags. Then we propose a method to solve this problem. Further discussion is carried out for the special case when the input signal is white Gaussian. It is shown that the convergence in the MSE sense occurs for step size range that is significantly smaller than the one necessary for the convergence of the mean. Simulation experiments are presented to support the obtained analytical results.

A new numerical procedure called asymptotic periodic waveform evaluation (APWE) for finding the steady state solution of nonlinear circuits driven by one tone periodic input signal is presented. APWE starts by constructing a virtual system which gives the same periodic steady state waveform as the original system's but with a shorter transient duration. Thus the periodic steady state (PSS) response can be obtained by simply performing transient analysis of the newly derived system for a few periods. An efficient method for solving the nonlinear equations occurred during the transient analysis is presented. To improve the convergence rate of PSS waveform, APWE is combined with extrapolation method. Some simulation results are shown.