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MATLAB : Fourier transform

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By Nuno Nogueira, CC BY-SA 2.5, https://commons.wikimedia.org/w/index.php?curid=3912826 MATLAB has been  crucial programming language across worldwide that let us express matrix and array mathematics directly. In signal processing and communication it plays vital role in analysing and exploring time series data in time domain or frequency domain. For analysing non periodic signals in frequency domain we use Fourier transform instead of Fourier series ,which is used to express periodic signals in terms of infinite sum of sinusoidal terms .   Fourier transform can exist for :      1. Energy signals      2. Power signals       3. Impulse signals  That means absolutely integrable signals can have their Fourier transform only.  Formula for Fourier transform;   Then its come to use Fourier transform in MATLAB. So here is the code for Fourier transform of sinusoidal wave , for any other signal we ...
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Memristor : brain-on-a-chip

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memristor


In the field of AI, researchers are working on devices having their own memory and ability of thinking, they are trying to mimic the human brain. The human brain is the most complicated structure consisting of millions of neurons that are interlinked by a thread-like structure called synapses.

The engineers from the Massachusetts Institute of Technology have designed 'brain-on -a-chip'. The chip is smaller than a piece of confetti, that is about 1 mm in dimension and made from thousands of artificial brain synapses known as Memristors. Memristors are the silicon-based component that mimics the information-transmitting synapses in the human brain.

Memristors or memory resistors are the necessary elements of neuromorphic computing. In a neuromorphic device, memristors would work more similar to a brain synapse. The synapse receives signals from one neuron, in the form of ions, and sends a corresponding signal to the next neuron. Like a brain synapse, a memristor would also be able to remember the value of associated with given current strength and produce exactly the same signal the next time it receives a similar current.

However, the existing memristor designs are limited in their performance. A single memristor is made of a positive and negative electrode, separated by a switching medium, or space between the electrodes. when a voltage applied to one electrode, ions from that electrode flow through the medium and forming the conduction channel to the other electrode. The received ions produce the electrical signals that the memristor transmits through the circuit.  

The team of the researcher first fabricated a negative electrode out of silicon, then made a positive electrode by depositing a slight amount of copper, followed by a layer of silver. They sandwiched the two electrodes around an amorphous silicon medium. In this way, they patterned a millimetre-square silicon chip with tens of thousands of memristor. 

Kim a researcher from MIT says that existing memristor design works pretty well in the case where voltage stimulates a large conduction channel or a heavy flow of ions from one electrode to other. But these designs are less reliable when memristors need to generate narrow signals, via thinner conduction channel.

Memristor could advance the development of small, portable AI devices.


-by Anshul Shakya

original written by Jennifer Chu.

source:- Massachusetts Insitute of Technology

Student at National Institute of Technology, Patna, Bihar (India).

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