P. K. Gaikwad

Development of Ag/WO3/ITO Thin Film Memristor Using Spray Pyrolysis Method

The unique nonlinear relationship between charge and magnetic flux along with the pinched hysteresis loop in I-V plane provide memory with resistance combinations of attribute to Memristor which lead to their novel applications in non volatile memory, nonlinear dynamics, analog computations and neuromorphic biological systems etc. The present paper reports development of Ag/WO3/ITO thin film memristor device using spray pyrolysis method. The structural, morphological and electrical properties of the thin film memristor device are further characterized using x-ray diffraction (XRD), Scanning Electron Microscopy (SEM), and semiconductor device analyzer. The memristor is simulated using linear dopent drift model to ascertain the theoretical and experimental conformations. For the simulation purpose, the width of doped region (w) limited to the interval [0, D] is considered as a state variable along with the window function characterized by the equation f (x) = w (1 − w). The reported memristor device exhibits the symmetric pinched hysteresis loop in I-V plane within the low operating voltage (±1 V).

Modelling of nanostructured memristor device characteristics using Artificial Neural Network (ANN)

Abstract The present paper reports modelling of nanostructured memristor device characteristics using Artificial Neural Network (ANN). The memristor is simulated using linear drift model and data generated thereof is applied for learning, testing and validation of ANN architecture. In the present investigation we demonstrate optimum ANN architecture for the said modelling by varying the number of hidden neurons and percentage of testing data. The percentage of validation data is varied in order to accomplish tuning of the experiment. Performance of ANN architecture thus derived has been measured in terms of Mean Squared Error (MSE) and Pearson correlation coefficient (r). The hidden units consist of nonlinear sigmoid activation functions and training algorithm is based on a Levenberg–Marquardt Backpropogation method. The reported ANN architecture reveals best performance at lower numbers of hidden neurons and further lower percentage of testing and validation data. Additionally, optimized ANN structure is selected for modelling of other characteristics of memristor such as, flux-charge relation, time domain memristance and width of doped region. The results support, ANN as the preeminent tool for modelling of nonlinear devices such as memristor and the suite of other emerging nanoelectronics devices.

Development of FPGA Based Network on Chip for Circumventing Spam

With the growing popularity of Internet and extensive use of E-mail as a communication media, the volume of Spam mails has seen to be growing at a phenomenal rate. The growing volume of Spam mails as well as their mutating nature annoys people and affects work efficiency significantly. The unsolicited emails or Spam’s used to be deliberated of as just a nuisance, in the past few decades, however in the last few years; their annoyance has reached to epidemic proportions. Thus the Spam mails have has really become a nightmare for every email user. This chapter presents Anti-Spam solution prototyped on Xilinx Spartan 3e FPGA and designed using Handel C. We have adopted the hardware-software co-design methodology and the same is described from scratch. Two IP cores have been designed viz. Content Addressable Memory (CAM) and Bloom Filter in Handel C and the same have been deployed on the Spartan 3e FPGA along with the customizable version of Microblaze. The main contribution is reporting the technical know how related to the co-design aspects that comprehends synergic mixture of soft IP cores of the content addressable memory (CAM) and bloom filter realized both in hardware and software with the Xilinx Microblaze processor. The toolset used for the hardware-software co-design is the Xilinx Embedded Design Kit (EDK). The design flow comprises of the IP core design in Handel-C, embedded in EDK driven by the central customized core of Microblaze.

Harnessing VLSI system design with EDA tools

Introduction.- Development of FPGA Based Network on Chip for Circumventing Spam.- Analog Front End and FPGA Based Soft IP Core for ECG Logger.- FPGA Based Multifunction Interface for Embedded Applications.- FPGA Based High Resolution Time to Digital Converter.

FPGA Based High Resolution Time to Digital Converter

In an increasingly digital domain of applications, the Digital Signal Processing (DSP) has become inevitable. With the outside environment predominantly analog, its conversion into the digital domain in order to facilitate the benefits of the matured DSP technology is also mandatory. Many a times the analog to digital converter performance becomes the bottleneck in advanced instrumentation and DSP applications. This chapter presents a Vernier Time to Digital Converter (TDC) with resolution less than 30 pS, implemented on SPARTAN III FPGA. Detailed description of the TDC using schematic editor and Verilog code ring oscillator, phase detector and counter have been described in this chapter.

FPGA Based Multifunction Interface for Embedded Applications

Embedding a soft IP core inside an FPGA has many advantages such as customization, design reuse, accelerating the design cycle and narrowing the time to market window thereby enhancing the productivity. In view of all the above mentioned advantages, the FPGA based systems are now penetrating the embedded arena which has marked the take off of the configware rather than the traditional embedded hardware and software. The complexity of the FPGA based SoCs in an Embedded paradigm has now been addressed by the designers by using the configware libraries that comprises of the soft IP cores. The design techniques pertaining to the soft IP cores are now regarded as the evolutionary techniques and the novel design methodologies of the Embedded Systems has comes out to be just an analytical marriage of the above mentioned soft IP cores. Pre-designed and pre-verified soft IP cores such as the ones designed in this chapter addresses the pertinent issues such as time to market, performance, area, power metrics etc. Further designing such soft IP cores in Handel C facilitates maximum flexibility and reconfigurability to match the requirements of a specific embedded design application. All the cores reported in this chapter have been verified/prototypes on the Xilinx Starter kit.