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Category: BTP
Tutorial: CMOS-Memristor based Neural Networks
AIM: To simulate a fully functional 2 layer CMOS-Memristor-based neural network for classification of benign and malign cancer. Description: The circuit-based neural network achieved an accuracy of 94.85% compared to the 96.71% accuracy of the original network. The trained weights were programmed onto the weight blocks of the memristor bridge in this neural network. Training of neural network was done on MATLAB and then weights were extracted and accordingly memristor-bridge weight blocks were configured. In the memristor-bridge circuit, currently resistors were used but they can be replaced with memristors. For activation function, we used ReLu (Rectified Linear Unit) and in…
CMOS-Memristor Hybrid Circuit for Edge Detection using NI Multisim and MATLAB
Hello, In this post, we will have a look at the following: Setting up 180nm/100nm MOSFET Models in Multisim Setting up a memristor model in NI MULTISIM A CMOS-Memristor hybrid circuit for edge detection Using MATLAB for image analysis NI Multisim is an excellent tool for simulation of both analog and digital circuits. One reason I like it over LTSpice or PSpice is the ease with which one can simulate mixed-signal circuitry. Using Multisim along with MATLAB allows conversion of image(pixel by pixel) to its a corresponding discrete voltage signal and vice versa. We can import PSPICE models to multisim…
An Investigation into Neuromorphic ICs using Memristor-CMOS Hybrid Circuits
Hi All, In this blog post, I’ve just copy-pasted my BTech Major project’s report. I hope someone will find this useful. You can also refer to the PDF of this blog post (Link), if you prefer that. Have Fun! ABSTRACT Memristors are passive two-terminal devices that behave similarly to variable resistors. The memristance of a memristor depends on the amount of charge flowing through it, and when the current stops flowing through it, it remembers the state. Thus, memristors are extremely suited for the implementation of memory units. Memristors find great application in neuromorphic circuits as it is possible to…
Memristors: Models, Window Functions, and their SPICE Simulations
This post mainly covers different famous memristor models, window functions along with their SPICE simulations(done on LTSPICE). The window function is used to add non-linearity at the boundaries. In contrast, Models are used to establish a linear/non-linear relationship between the rate of state change and the stimulus (current/voltage). Content: Models Linear Non-linear Threshold Macro-model Window functions Properties of window functions Types of window functions: Struckov Benderli Joglekar Biolek Prodomakis Jinxiang SPICE simulations Memristor Models Linear Ion drift Model (Ideal Model) In this model, there exists a linear relationship between the state derivative and the stimuli(Voltage/Current). It assumes that vacancies have…
Memristors : Motivation, Theory, and Feasibility
Memristors, the fourth missing element after Inductance, Resistance, and capacitance, is nowadays a scorching topic of research among the electronics community. A large number of papers on its models, applications, and feasibility are now available. In this post, I’ll try to cover most of its background research: Content:- Introduction What are memristors? Characteristics of a memristor Transistor vs. memristor The polarity of a memristor and an analogy Memristor links to chaos theory?[TBD] Motivation well-known problems with present-day computers limitations of CMOS technology Moore’s soul at unrest Theory History Before HP After HP HP’s model Memristive systems Problems with Chua’s memristor…