Memristive behavior has been clearly addressed through growth and shrinkage of thin filaments in metal-oxide junctions. Capacitance change has also been observed, raising the possibility of using them as memcapacitors. Therefore, this paper proves that metal-oxide junctions can behave as a memcapacitor element by analyzing its characteristics and modeling its memristive and memcapacitive behaviors. We develop two behavioral modeling techniques: charge-dependent memcapacitor model and voltage-dependent memcapacitor model. A new physical model for metal-oxide junctions is presented based on conducting filaments variations, and its effect on device capacitance and resistance. In this model, we apply the exponential nature of growth and shrinkage of thin filaments and use Simmons' tunneling equation to calculate the tunneling current. Simulation results show how the variations of practical device parameters can change the device behavior. They clarify the basic conditions for building a memcapacitor device with negligible change in resistance.

Large mutual capacitance touch screen panels (TSP) are susceptible to display and ambient noise. This paper presents a multi-touch detection algorithm using an efficient noise compensation technique for large mutual capacitance TSPs. The algorithm starts with a calibration technique to overcome TSP mutual capacitance variation. It also overcomes the shadow effect of a hand close to TSP and mutual capacitance variation by applying dynamic threshold calculations. Time and space filters are also used to filter out noise. Experimental results are used to determine system parameters for best performance.

Recently the demand for projected capacitance touch screens is sharply growing especially for large screens for medical devices, PC monitors and TVs. Large touch screens in general need a controller of higher complexity. They usually have a larger number of driving and sensing lines, and hence it takes longer to scan one frame for touch detection leading to a low frame scan rate. In this paper, a novel touch screen control technique is presented, which scans each frame in two steps of simultaneous multi-channel driving. The first step is to drive all driving lines simultaneously and determine which sensing lines have any touch. The second step is to sequentially rescan only the touched sensing lines, and determine exact positions of the touches. This technique can substantially increase the frame scan rate. This technique has been implemented using an FPGA and an AFE board, and tested using a commercial 23-inch touch screen panel. Experimental results show that the proposed technique improves the frame scan rate by 8.4 times for the 23-inch touch screen panel over conventional methods.

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Abstract-In 2008, the fourth passive element "Memristor" was implemented as a device having both passivity and nonvolatile properties opening the way into new possibilities in the design and fabrication of innovative memory, arithmetic and logic architectures. Nano-features and ionic transport mechanism inherent in memristor device introduce new challenges into modeling, characterization and, in particular, in the related circuit simulation needs with system constructs. Therefore, in this paper, we analyze memristor device fundamentally to characterize the memristance paying particular attention to the hidden memcapacitance effect. Our proposed macro-model modifies takes into account some of the non ideal effects like tunneling current and the hidden memcapacitor constructed across non conducting materials. The model provides the insight for building a device as either memristive or memcapacitive system. The simulation results have been compared with HP published data which show good agreement.