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Electrical Engineering
MATLAB
Matlab and Mathematica
Telecommunications Engineering
Wireless
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$10 USD / hodinu
Pochází z PAKISTAN
islamabad, pakistan
$10 USD / hodinu
Aktuálně je zde 8:12 odp.
Připojil se září 23, 2019
2 Doporučení

Mubashar S.

@mubashar06

 5,0 (30 recenze)
5,0
5,0
84%
84%
$10 USD / hodinu
Pochází z PAKISTAN
islamabad, pakistan
$10 USD / hodinu
97 %
Úspěšně realizované projekty
88 %
V rámci rozpočtu
91 %
Včas
18 %
Poměr opětovného zaměstnání

Matlab Programmer

An Electrical Engineer Specialized in Wireless Communication, With 5+ years of professional Experience in solving Engineering Problems (on Matlab), Digital simulations, Signal and Image Processing.
Freelancer Matlab and Mathematica Engineers Pakistan
Zobrazit všechny Matlab and Mathematica Engineers v Pakistan

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Portfolio

6933196
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
6933146
The simulation of adaptive beam former is carried out using the least mean square (LMS) algorithm and recursive least square (RLS) algorithm. It can be seen from simulations that, the RLS convergence is much faster than the LMS convergence.
BEAMFORMING with LMS & RLS
The simulation of adaptive beam former is carried out using the least mean square (LMS) algorithm and recursive least square (RLS) algorithm. It can be seen from simulations that, the RLS convergence is much faster than the LMS convergence.
BEAMFORMING with LMS & RLS
The simulation of adaptive beam former is carried out using the least mean square (LMS) algorithm and recursive least square (RLS) algorithm. It can be seen from simulations that, the RLS convergence is much faster than the LMS convergence.
BEAMFORMING with LMS & RLS
6441225
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
6441209
In this project the concept of correlation is used at the receiver end to recover the data. Bit Error Rate (Plots) are plotted against different SNRs.
Correlation in signal processing
In this project the concept of correlation is used at the receiver end to recover the data. Bit Error Rate (Plots) are plotted against different SNRs.
Correlation in signal processing
6441187
Leach mobility algorithm is implemented and its parameters are adjusted including clustering techniques (for Random mobility model) to generate the required results.
LEACH + Random Way Point
Leach mobility algorithm is implemented and its parameters are adjusted including clustering techniques (for Random mobility model) to generate the required results.
LEACH + Random Way Point
6441177
This problem examines the autocorrelation and power spectrum characteristics of a low-pass random process. The desired low-pass characteristics is achieved by passing a sequence of statistically independent random numbers through a digital low-pass filter with a given impulse response
Autocorrelation and Power Spectral Characteristics
This problem examines the autocorrelation and power spectrum characteristics of a low-pass random process. The desired low-pass characteristics is achieved by passing a sequence of statistically independent random numbers through a digital low-pass filter with a given impulse response
Autocorrelation and Power Spectral Characteristics
This problem examines the autocorrelation and power spectrum characteristics of a low-pass random process. The desired low-pass characteristics is achieved by passing a sequence of statistically independent random numbers through a digital low-pass filter with a given impulse response
Autocorrelation and Power Spectral Characteristics
This problem examines the autocorrelation and power spectrum characteristics of a low-pass random process. The desired low-pass characteristics is achieved by passing a sequence of statistically independent random numbers through a digital low-pass filter with a given impulse response
Autocorrelation and Power Spectral Characteristics
6933196
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
From the 'N' number of nodes, only selected nodes will transmit their data depending upon the requirements.
Data transmission of selective nodes in WSN
6933146
The simulation of adaptive beam former is carried out using the least mean square (LMS) algorithm and recursive least square (RLS) algorithm. It can be seen from simulations that, the RLS convergence is much faster than the LMS convergence.
BEAMFORMING with LMS & RLS
The simulation of adaptive beam former is carried out using the least mean square (LMS) algorithm and recursive least square (RLS) algorithm. It can be seen from simulations that, the RLS convergence is much faster than the LMS convergence.
BEAMFORMING with LMS & RLS
The simulation of adaptive beam former is carried out using the least mean square (LMS) algorithm and recursive least square (RLS) algorithm. It can be seen from simulations that, the RLS convergence is much faster than the LMS convergence.
BEAMFORMING with LMS & RLS
6441225
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
Multiple modulation formats are detected at the receiver including M-FSK, M-PAM and M-QAM. Sparse-FFT is used to boost the detection time by compromising detection accuracy.
Modulation formats identification using sparse-FFT
6441209
In this project the concept of correlation is used at the receiver end to recover the data. Bit Error Rate (Plots) are plotted against different SNRs.
Correlation in signal processing
In this project the concept of correlation is used at the receiver end to recover the data. Bit Error Rate (Plots) are plotted against different SNRs.
Correlation in signal processing
6441187
Leach mobility algorithm is implemented and its parameters are adjusted including clustering techniques (for Random mobility model) to generate the required results.
LEACH + Random Way Point
Leach mobility algorithm is implemented and its parameters are adjusted including clustering techniques (for Random mobility model) to generate the required results.
LEACH + Random Way Point
6441177
This problem examines the autocorrelation and power spectrum characteristics of a low-pass random process. The desired low-pass characteristics is achieved by passing a sequence of statistically independent random numbers through a digital low-pass filter with a given impulse response
Autocorrelation and Power Spectral Characteristics
This problem examines the autocorrelation and power spectrum characteristics of a low-pass random process. The desired low-pass characteristics is achieved by passing a sequence of statistically independent random numbers through a digital low-pass filter with a given impulse response
Autocorrelation and Power Spectral Characteristics
This problem examines the autocorrelation and power spectrum characteristics of a low-pass random process. The desired low-pass characteristics is achieved by passing a sequence of statistically independent random numbers through a digital low-pass filter with a given impulse response
Autocorrelation and Power Spectral Characteristics
This problem examines the autocorrelation and power spectrum characteristics of a low-pass random process. The desired low-pass characteristics is achieved by passing a sequence of statistically independent random numbers through a digital low-pass filter with a given impulse response
Autocorrelation and Power Spectral Characteristics

Recenze

Změny byly uloženy
Zobrazeno 1 - 5 z 30 recenzí
Filtrovat recenze podle:
1,0
$30,00 USD
Matlab code
simply a scammer who is looking for easy money by scamming people and wasting their time.
Engineering
Matlab and Mathematica
Electrical Engineering
Mathematics
Antenna Measurements
W
Pochází z Abdulrahman A.
@whatsthepoint0
•
před 3 roky
5,0
$50,00 USD
Central Limit Theorem -- 3
Very smart person, who’s do the work when he accepted the project.
Wireless
Matlab and Mathematica
Electrical Engineering
Telecommunications Engineering
+1 dalších
F
Pochází z Amad K.
@fbuenter
•
před 3 roky
5,0
$235,00 USD
Project 29224559 has been deleted
" Everything was perfect!" He is very dedicated person who puts lot of effort for his work. Great communication. Also, He ensured his availability at all times. He is deeply Knowledgeable and was on hand to answer all questions. Highly recommend working with him. Trustworthy freelancer.
Avatar uživatele
Pochází z Nithya Subramani S.
@Nithzsparkz
•
před 3 roky
5,0
$440,00 NZD
Project for Mubashar S.
The project delivered on time and within budget. The working was perfect and I won't hesitate to work with him again. Thank you so much.
Wireless
Matlab and Mathematica
Electrical Engineering
Telecommunications Engineering
+1 dalších
A
Pochází z Anas A.
@anas1809
•
před 4 roky
5,0
$40,00 AUD
wavelets analysis
He is very good, responsive and communicates very well. I will hire him again.
Matlab and Mathematica
A
Pochází z Kwame A.
@ATOKWAMEST
•
před 4 roky

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Ověření

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Top dovednosti

Matlab and Mathematica 27
Electrical Engineering 24
Telecommunications Engineering 17
Wireless 16
MATLAB 16

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