DFT and FFT with Python and It is applications on various signals

Fast Fourier Transform (FFT) is one of the most important algorithms in computer science, electronics and signal processing engineering. It is a fast solver for Discrete Fourier Transform (DFT). Basically, DFT or FFT transforms signals from time-amplitude domain to frequency-amplitude domain. The reverse form of the FFT is known as Inverse Fast Fourier Transform which converts, naturally, signals from frequency domain to time domain.

FFT is heavily used in communication, radar or computer systems. For example OFDM (orthogonal frequency division multiplexing) is developed based on IFFT and FFT. Since Python is most common used scientific programming language beside Matlab, I would like to present some information about FFT and using it in Python.

Python or Koala 


This blog post (https://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/) includes the basics of the FFT and very clear comparison of  it to DFT. Another blog post (https://www.ritchievink.com/blog/2017/04/23/understanding-the-fourier-transform-by-example/) which includes a very good example of the FFT. This page (https://plot.ly/python/fft-filters/) has FFT filters using Python. An OFDM example which utilizes FFT and IFFT in Python is presented here (https://dspillustrations.com/pages/posts/misc/python-ofdm-example.html) .

An extra link: (http://www.music.helsinki.fi/tmt/opetus/uusmedia/esim/index-e.html) in which you can find some .wav sound examples to process using FFT. An application of short-term FFT on sounds: short term 
Sound Processing with Short Time Fourier Transform

Another working Python example of the short-term FFT which examine .wav files to find out power of the sound at specific frequency and time blocks.


The Difference Between Artificial Intelligence and Machine Learning


I think the first question which must be answered clearly while starting teaching artificial intelligence and machine learning should be about the difference between them.

AI - Artificial Intelligence is a comprehensive concept that stating that the computers can learn, think and decide what they should do by themselves in every situation. However, fully AI concept is not possible at the moment as various operations such as image recognition, playing a game, creative thinking etc. require different algorithms which are striving to solve specific problems and tasks.

ML - Machine Learning is the specific application of AI, which is mostly relying on learning based on historical data to analyze future data and decide using these analyzes. It can be categorized into supervised and unsupervised learning. Former one utilizes the labelled data to train the machine learning core (brain) and the latter one uses an agent in order to solve the problems. Machine learning algorithms are generally trained in order to solve one or a few specific problems, consequently, they cannot find answers to every question or problem that you may ask or have.
An Image illustrating imaginary neural networks and neural nodes  

More information can be found on the following links with some examples:

What is MIMO Communication in 4G and WiFi Networks ?

Recently, the wireless communication systems have been transformed and now they have more robust communication link and higher spectral efficiency. One of the main improvement, which has been implemented into current 4G and WiFi networks, is MIMO (Multiple-Input Multiple-Output) technique.

MIMO communication networks include more than one transmitter and receiver antennas in order to use multiple channel at the same time and frequency resources. The idea behind this technique is each antenna port can have a separate channel due to reflection and the scattering of the microwaves during the propagation. These channels are utilized using software based receivers and equalizer in order to simultaneously transmit data.


MIMO enhances the spectral efficiency, thus the capacity of the link besides providing more communication links.  

Polarisation of Electromagnetic Waves



The polarisation of electric field states the orientation and magnitude of its field vectors and their alteration through the time. Polarisation is related to the transverse electromagnetic waves (TEM), in which directions and magnitudes of both electric and magnetic fields vary by time. Polarisation of EM waves from an antenna is classified into three main categories: linear, circular or elliptical polarisations. Furthermore, the direction of polarisation may be clockwise (CW, right-hand polarisation) or counter-clockwise (CCW, left-hand polarisation). For instance, the equation indicates a circularly polarized wave which consists of two components in the x and y directions. If polarisation of the receiver antenna does not match with the polarisation of incoming waves, the amplitudes of the received waves decrease. This polarisation mismatch will cause polarisation loss and reduce the power of the received signal. On the other hand, polarisation discrepancy can be employed to transmit two signals simultaneously at the same frequency-time resources using two different polarisations such as in satellite communication.



Antenna polarisation is another opportunity for MIMO systems. Because the vertical and horizontal polarisation may be utilized to increase the number of antennas in a given area. Single polarized and dual polarized 2\times2 MIMO systems have been compared [1], in which they show that if there is a high correlation between two antennas, then polarized MIMO have better performance over a single polarized system. In another similar study, they perform broadband outdoor channel measurement to verify the performance of 2x3 dual-polarized MIMO system at 2.5 GHz frequency and they achieved higher capacity using dual polarisation especially in the close range. On the other hand, aforementioned two studies demonstrate that if the distance between transmitter and receiver is large enough, then single polarised MIMO system performs better than the dual polarised system.

Graphene enhanced devices simulation based design microwave optical frequencies | Video

Graphene is a material with extraordinary properties. It promises to open up new application areas or to enhance existing devices, as indicated by a large amount of research on this topic. Currently, commercial applications are still small in number but increasing. EM simulations are a formidable tool to aid in the research and design of new devices that employ graphene.

Artificial Intelligence with Python and Machine Learning examples


Firstly, the theory of the Artificial Intelligence and then you will find some useful examples of how to use Python for Machine learning and artificial intelligence applications.





Note, before using them, you will probably have to install some packages (e.g. TensorFlow) on your computer.





Simulation of electromagnetic wave with Python

Antenna arrays and python



 These links include information about how to model and calculate patch antenna arrays using python:




  1. https://medium.com/@johngrant/antenna-arrays-and-python-introduction-8e3b612ecdfb
  2. https://medium.com/@johngrant/antenna-arrays-and-python-square-patch-element-6bd3445f39d5
  3. https://medium.com/@johngrant/antenna-arrays-and-python-the-array-finally-3613966153d7
  4. https://medium.com/@johngrant/antenna-arrays-and-python-plotting-with-pyplot-ae895236396a
  5. https://medium.com/python-pandemonium/antenna-arrays-and-python-calculating-directivity-84a2cfea0739


I would like to remind you that in feeding a patch antenna, the location of the feed point determines the patch's input impedance at the resonance frequency. If feeding with standard 50Ohm SMA connectors, the input impedance of the patch should be adjusted to approx. 50Ohm for optimum matching.Now keep in mind that you don't want the feed location to be neither at the edge of the patch nor at the center. The reason is that (using the cavity model for analyzing the patch and assuming the dominant mode) the E field is zero at the center of the patch (so this would give you zero input impedance) and maximum at the edges (implying very high input impedance). So you generally want to be somewhere in between the edge and the middle to achieve 50Ohm.The rule of thumb is approx 1/3 of the distance between the two edges.Any book for microstrip antennas should have the formulas you need to find the location of the feed point, to obtain precisely 50Ohm input impedance. My calculation gave me that you need to place your feed at about 12.88 mm from the edge.
http://www.edaboard.com/showthread.php?t=203704

Video Game Industry in The World

One of the biggest digital industries in the world is the game industry which includes mobile games, console games and PC games.  UK, USA, Japan, Canada, Korea and China have huge market shares in this industry.

Market Share of Game Development around the world. [1]

The web pages below present market share of the game industry by countries and which countries are leading this industry.


  1. http://www.gameindustrycareerguide.com/best-cities-for-video-game-development-jobs/
  2. https://www.gamedesigning.org/game-development-studios/
  3. https://www.gamedevmap.com/     gives extensive information about which company is in which city/country
  4. https://venturebeat.com/2014/06/24/gamer-globe-the-top-100-countries-by-2014-game-revenue/
  5. http://uk.businessinsider.com/coolest-video-game-companies-in-europe-2015-7/#hello-games-is-working-on-a-game-loved-by-both-kanye-west-and-elon-musk-31

Notes


Japan Graduate School Directory
04 Nov 2016
http://www.jpss.jp/en/search/

via this link we can conduct MSc or PhD programs in Japan.

Ultra Wideband Antenna Design for Target Detection
04 Nov 2016
Abstract—In this paper, a four-element microstrip antenna array is presented. The array is composed of Wilkinson power dividers which act as feed network along with Dolph-Chebyshev distribution and four identical patch antenna elements. The array elements are properly designed to have a compact size and constant gain against frequency. The simulated results show good agreement with the measured results for the fabricated antenna array. Measurement shows that the array has a peak gain of more than 12 dBi with side-lobe level of −15 dB at 6 GHz. These characteristics make the antenna array suitable for UWB directional uses.