The following resources come from the 2009/10 BSc (Hons) in Multimedia Technology (course number 2ELE0075) from the University of Hertfordshire. All the mini projects are designed as level two modules of the undergraduate programmes.
The objectives of this project are to demonstrate abilities to:
• Handle camera setup, calibrate and capture still and video faces
• Pre-process images and extract features
• Perform face recognition by a) using existing methods and b) trying new techniques.
This project requires the students to apply their abilities to handle image capture hardware and software. Since this is an active area of research, students will need to perform literature survey and discuss ( through brainstorm sessions) their performance characteristics. In addition, they will need to design and implement pre-processing and recognition codes leading to face recognition.
The following resources come from the 2009/10 BSc (Hons) in Multimedia Technology (course number 2ELE0075) from the University of Hertfordshire. All the mini projects are designed as level two modules of the undergraduate programmes.
The objectives of this project are to demonstrate abilities to:
• Handle camera setup, calibrate and capture still and video faces
• Pre-process images and extract features
• Perform face recognition by a) using existing methods and b) trying new techniques.
This project requires the students to apply their abilities to handle image capture hardware and software. Since this is an active area of research, students will need to perform literature survey and discuss ( through brainstorm sessions) their performance characteristics. In addition, they will need to design and implement pre-processing and recognition codes leading to face recognition.
This lecture we will do some practice on Basic MATLAB Scripts.
We will start with simple scripts and will discuss some electrical engineering applications.
Applications include simple electrical calculations and electrical machine models.
The frame work that I used for my Introduction to Matlab hour long course. Most of the instruction took place on a live Matlab screen, but this provided the framework
This is the Complete course of C Programming Language for Beginners. All Topics of C programming Language are covered in this single power point presentation.
Visit: www.cyberlabzone.com
Part of Lecture Series on Automatic Control Systems delivered by me to Final year Diploma in Engg. Students. Equally useful for higher level. Easy language and step by step procedure for drawing Bode Plots. Three illustrative examples are included.
In this presentation we described important things about Image processing and computer vision. If you have any query about this presentation then feels free to visit us at:
http://www.siliconmentor.com/
This is the first part of the presentation series on one of the powerful open sources libraries, the opencv. this presentation is about the introduction, installation, some basic functions on images and some basic image processing on the images
Presentation on Face detection and recognition - Credits goes to Mr Shriram, "https://www.hackster.io/sriram17ei/facial-recognition-opencv-python-9bc724"
This lecture we will do some practice on Basic MATLAB Scripts.
We will start with simple scripts and will discuss some electrical engineering applications.
Applications include simple electrical calculations and electrical machine models.
The frame work that I used for my Introduction to Matlab hour long course. Most of the instruction took place on a live Matlab screen, but this provided the framework
This is the Complete course of C Programming Language for Beginners. All Topics of C programming Language are covered in this single power point presentation.
Visit: www.cyberlabzone.com
Part of Lecture Series on Automatic Control Systems delivered by me to Final year Diploma in Engg. Students. Equally useful for higher level. Easy language and step by step procedure for drawing Bode Plots. Three illustrative examples are included.
In this presentation we described important things about Image processing and computer vision. If you have any query about this presentation then feels free to visit us at:
http://www.siliconmentor.com/
This is the first part of the presentation series on one of the powerful open sources libraries, the opencv. this presentation is about the introduction, installation, some basic functions on images and some basic image processing on the images
Presentation on Face detection and recognition - Credits goes to Mr Shriram, "https://www.hackster.io/sriram17ei/facial-recognition-opencv-python-9bc724"
A basic overview, application and usage of MATLAB for engineers. It covered very basics essential that will help one to get started with MATLAB programming easily.
Provided by IDEAS2IGNITE
CDMA Transmitter and Receiver Implementation Using FPGAIOSR Journals
Abstract: Code Division Multiple Access (CDMA) is a spread spectrum technique that uses neither frequency channels nor time slots. With CDMA, the narrow band message (typically digitized voice data) is multiplied by a large bandwidth signal that is a pseudo random noise code (PN code). All users in a CDMA system use the same frequency band and transmit simultaneously. The transmitted signal is recovered by correlating the received signal with the PN code used by the transmitter. The DS - CDMA is expected to be the major medium access technology in the future mobile systems owing to its potential capacity enhancement and the robustness against noise. The CDMA is uniquely featured by its spectrum-spreading randomization process employing a pseudo-noise (PN) sequence, thus is often called the spread spectrum multiple access (SSMA). As different CDMA users take different PN sequences, each CDMA receiver can discriminate and detect its own signal, by regarding the signals transmitted by other users as noise- like interferences. In this project direct sequence principle based CDMA transmitter and receiver is implemented in VHDL for FPGA. Modelsim 6.2(MXE) tool will be used for functional and logic verification at each block. The Xilinx synthesis technology (XST) of Xilinx ISE 9.2i tool will be used for synthesis of transmitter and receiver on FPGA Spartan 3E. Keywords: CDMA, DSSS, BPSK, GOLD code.
This MATLAB section of source code covers MATLAB based projects.
Download free source code viz. FIR,IIR,scrambler,interleaver,FFT,convolution,correlation,interpolation,decimation,CRC,impairments,data type conversions and more.
RS encoder,convolutional encoder,viterbi decoder,OFDM,OFDMA,MIMO is also covered.WiMAX,WLAN,LTE source codes are also provided.
In a communications system, the channel is affected by an additive white Gaussian noise (AWGN)
and a fading due to a distance between a transmitter and a receiver. Especially, there are many kinds of
channel fadings. Depending on the moving speeds of transmitters or receivers, a fading type can be a slow
fading or a fast fading (i.e., the product of 0.1 and coherence time than smaller or larger than the symbol
period of signal are corresponding to fast and slow fadings). Moreover, a channel can be referred as a
selective fading or a flat fading corresponding to the product of 0.1 and coherence bandwidth than smaller
or larger than the bandwidth of signal. These above effects can suffer received signals at a destination.
Hence the performance of received signals in term of bit-error-rate (BER) is much degraded.
In order to overcome these issues, communications systems would be carefully designed. In detail,
application systems operating over the AWGN channels would use coding schemes to combat an additive
white noise. However, if environment is affected by fading, coding techniques only solve a fast fading.
It implies that, coding schemes degrade received signals when they go through slow fading channels. In
this case, an interleaving technique would be added to a communications system. In order to overcome
the fading channels, besides, using an interleaver as above, we can exploit the diversity of multi-path. It
implies that the effects of fading can be combated by transmitting the original signals over multiple paths
(experiencing independent fading) and then combining all received signals at the receiver. There are many
kinds of diversities to mitigate this issue, such as diversity in time, frequency, and space. Correspondingly,
a lot of state-of-art methods are given, viz. diversity receiving and transmitting, OFDM, space-time block
codes, MIMO, Cooperation and etc.
In summary, the main scope of this report is modeling a communications system. First, I create a
basic communications system, where it includes the modulation/demodulation using a QPSK modulation,
a channel type is an AWGN channel. Secondly, a coder/decoder scheme is added to a transmitter/receiver to
improve received signals. Thirdly, the fading channel is considered when a receiver/transmitter is moving.
It means that the slow fading is mentioned. The performance is shown to prove that the received signal
2
is degraded whether a coding scheme is used or not. Finally, an interleaver/deinterleaver is used to solve
this problem.
Besides, the performance in terms of BER is used to verify a validity of these above techniques in a
communications system.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
http://www.cetpainfotech.com
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
TeeChart adalah komponen pembuatan bagan tujuan umum yang dirancang untuk digunakan dalam lingkup yang berbeda, menawarkan berbagai macam estetika untuk memetakan data. Umumnya TeeCharts diterbitkan di lapangan, di area di mana sejumlah besar data harus diinterpretasikan secara teratur, tetap berdasarkan pilihan desainer dalam bentuk yang paling sederhana untuk memaksimalkan "rasio data-tinta". Sloan Digital Sky Survey , penggunaan SDSS Web Services untuk memetakan "Ilmiah .. merencanakan data online" di The Virtual Observatory Spectrum Services mencerminkan pendekatan itu. Penulis grafik SDSS memilih untuk mewakili data menggunakan tampilan garis 2D standar TeeChart. Kecepatan juga merupakan faktor saat memilih cara paling efektif memplot data. Data waktu nyata, pada frekuensi hingga puluhan atau ratusan titik data atau lebih per detik, memerlukan pendekatan ekonomis prosesor paling banyak untuk pembuatan bagan. Waktu pemrosesan komputer yang didedikasikan untuk plotting data harus seringan mungkin, membebaskan tugas-tugas komputer "untuk mencapai akuisisi, tampilan, dan analisis data secara real-time".
PID Tuning using Ziegler Nicholas - MATLAB ApproachWaleed El-Badry
This is an unreleased lab for undergraduate Mechatronics students to know how to practice Ziegler Nicholas method to find the PID factors using MATLAB.
ENG3104 Engineering Simulations and Computations Semester 2, 2.docxYASHU40
ENG3104 Engineering Simulations and Computations Semester 2, 2015
Assessment: Assignment 3
Due: 23 October 2015
Marks: 300
Value: 30%
1 (worth 40 marks)
1.1 Introduction
To assess how useful the wind power could be as an energy source, use the file ass2data.xls to
calculate the total energy available in the wind for each year of data.
1.2 Requirements
For this assessment item, you must produce MATLAB code which:
1. Calculates the total energy for each of the years.
2. Reports to the Command Window the energy for each year.
3. Briefly discusses whether there is any trend in the results for annual energy production.
4. Has appropriate comments throughout.
You must also calculate the total energy for the first four hours of power data (i.e. over
the first five data entries) by hand to verify your code; submit this working in a pdf file.
Your MATLAB code must test (verify) whether the computed value of energy is the same as
calculated by hand.
1.3 Assessment Criteria
Your code will be assessed using the following scheme. Note that you are marked based on how
well you perform for each category, so the correct answer determined in a basic way will receive
half marks and the correct answer determined using an excellent method/code will receive full
marks.
Quality of the code 5 marks
Quality of header(s) and comments 5 marks
Quality of calculation of the energy for each year 15 marks
Quality of reporting 5 marks
Quality of discussion 5 marks
Quality of verification based on hand calculations 5 marks
1
ENG3104 Engineering Simulations and Computations Semester 2, 2015
2 (worth 65 marks)
2.1 Introduction
For the wind turbines to operate effectively, they must turn to face into the wind. This could
create large stresses in the structure if the wind changes direction quickly while the wind speed
is high. You are to assess if this is likely to happen using the data in ass2data.xls.
2.2 Requirements
For this assessment item, you must produce MATLAB code which:
1. Calculates the instantaneous rate of change of wind direction using:
(a) backward differences
(b) forward differences
(c) central differences
2. Plots the three sets of derivatives as functions of time.
3. Produces scatter plots of maximum wind gust as functions of each of the derivatives.
4. Displays a message in the Command Window with a brief discussion of the scatter plots.
Discuss which of the derivatives should be used to compare with the wind gust and why.
Discuss whether you think the wind changes direction too quickly while the wind speed
is high and why.
5. Has appropriate comments throughout.
You must also use a backward difference, forward difference and central difference by hand to
determine the rate of change of wind direction for the twelfth data entry; submit this working
in a pdf file. Your MATLAB code must test (verify) whether these values are the same as
computed by the code for the three differences.
2.3 Assessment Criteria
Your code will ...
MATLAB DOCUMENTATION ON SOME OF THE MODULES
A.Generate videos in which a skeleton of a person doing the following Gestures.
1.Tilting his head to right and left
2.Tilting his hand to right and left
3.Walking
in matlab.
B. Write a MATLAB program that converts a decimal number to Roman number and vice versa.
C.Using EZ plot & anonymous functions plot the following:
· Y=Sqrt(X)
· Y= X^2
· Y=e^(-XY)
D.Take your picture and
· Show R, G, B channels along with RGB Image in same figure using sub figure.
· Convert into HSV( Hue, saturation and value) and show the H,S,V channels along with HSV image
E.Record your name pronounced by yourself. Try to display the signal(name) in a plot vs Time, using matlab.
F.Write a script to open a new figure and plot five circles, all centered at the origin and with increasing radii. Set the line width for each circle to something thick (at least 2 points), and use the colors from a 5-color jet colormap (jet).
G. NEWTON RAPHSON AND SECANT METHOD
H.Write any one of the program to do following things using file concept.
1.Create or Open a file
2. Read data from the file and write data to another file
3. Append some text to already existed file
4. Close the file
I.Write a function to perform following set operations
1.Union of A and B
2. Intersection of A and B
3. Complement of A and B
(Assume A= {1, 2, 3, 4, 5, 6}, B= {2, 4, 6})
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
2. What is Simulink
• Simulink is an input/output device GUI block diagram
simulator.
• Simulink contains a Library Editor of tools from which we
can build input/output devices and continuous and
discrete time model simulations.
• To open Simulink, type in the MATLAB work space
– >>simulink
3. The Library Editor
• >>simulink
• Simulink opens with
the Library Browser
• Library Browser is
used to build
simulation models
10. Signal Routing
• Simulink Extras: additional
linear provide added block
diagram models. The two
PID controller models are
especially useful for PID
controller simulation.
11. Building Models
• Creating a New Model
• To create a new model, click the New button on the
Library Browser’s toolbar
• This opens a new untitled model window.
12. Building Models (2)
• Model elements are added by selecting the appropriate
elements from the Library Browser and dragging them
into the Model window. Alternately, they may be copied
from the Library Browser and pasted into the model
window.
• To illustrate lets model the capacitor charging equation:
15. Connecting the System Blocks
System blocks are connected in to ways; one way is the auto
connect method which is done by 1st selecting the source block
and holding down the Cntr key and selecting the destination
block.
Simulink also allows you to draw lines manually between blocks
or between lines and blocks. To connect the output port of one
block to the input port of another block: Position the cursor over
the first block’s output port. The cursor shape changes to
crosshairs. Right click and drag the crosshairs to the input of the
destination block to make the connection.
The next slide shows the connected model
17. Editing the Capacitor Model
Now that we have connected the model, we need to edit it. This
is done by selecting and double clicking to open the appropriate
models and then editing. The blocks we need to edit are the
step function, the two gain blocks, and the summing junction
block.
18. Editing the Capacitor Model (2)
In editing the blocks note that we have set the height of the step
function at 10, left R and C as variable (we will enter these from
the workspace), and changed the sign of the summing junction
input from + to -.
20. Controlling the Simulation - Solver
Simulink uses numerical integration to solve dynamic system
equations. Solver is the engine used for numerical integration.
Key parameters are the Start and Stop times, and the Solver
Type and methods.
21. Solver Parameters
The Start and Stop times set the start and stop times for the
simulation.
Solver Type sets the method of numerical integration as variable
step or fixed step. Variable step continuously adjusts the
integration step size so as to speed up the simulation time.
I.E., variable step size reduces the step size when a model’s
states are changing rapidly to maintain accuracy and increases
the step size when the system’s states are changing slowly in
order to avoid taking unnecessary steps.
Fixed step uses the same fixed step size throughout the
simulation. When choosing fixed step it is necessary to set the
step size.
22. Setting Fixed Step Size
The following example illustrates setting the fixed step size to a
value of 0.01 seconds.
23. Setting Fixed Step Size
The following example illustrates setting the fixed step size to a
value of 0.01 seconds.
24. Setting the Integration Type
The list of integration type solvers are shown below. For more
information on fixed and variable step methods and integration
types consult the MATLAB Simulink tutorial.
25. Running the Simulation
To run the simulation we 1st need to enter the values of R and
C. Note we could have entered these directly in the gain blocks
but we chose to enter these from the work space. To do this in
the work space we type
>>R = 1; C = 1;
This will fix the gain block’s as K = 1/(R*C)
Now select and click
the run button to run
the simulation
26. Viewing the Simulation with the Scope
To view the simulation results double click on the Scope block to
get. To get a better view left click and select Autoscale
27. Setting the Scope Axis Properties
We can adjust the Scope axis properties to set the axis limits:
28. Setting the Scope Parameters
The default settings for the Scope is a Data History of 5000 data
samples. By selecting Parameters an un-clicking the Limit
data points to last 5000 we can display an unlimited number of
simulation samples. Especially useful for long simulations or
simulations with very small time steps.
29. Saving Data to the Work Space
Often we wish to save data to the work space and use the
MATLAB plot commands to display the data. To do this we can
use the Sink Out1 block to capture the data we wish to display.
In this example we will connect Out blocks to both the input and
the output as shown below:
30. Where does the Output Data get Saved
To see where the output data gets saved we open Solver and
select Data Import/Export and unclick the Limit data points to
last box. As shown time is stored as tout, and the outputs as
yout.
31. Where does the Output Data get Saved
Now run the simulation and go to the workspace and type whos
Note that yout is a 1001 by 2 vector, that means that yout(:,
1)=input samples, and yout(:,2)=output samples.
To plot the data execute the M-File script shown on the next
slide.
32. M-File Script to Plot Simulink Data
' M-File script to plot simulation data '
plot(tout,yout(:,1),tout,yout(:,2)); % values to plot
xlabel('Time (secs)'); grid;
ylabel('Amplitude (volts)');
st1 = 'Capacitor Voltage Plot: R = '
st2 = num2str(R); % convert R value to string
st3 = ' Omega'; % Greek symbol for Ohm
st4 = ', C = ';
st5 = num2str(C);
st6 = ' F';
stitle = strcat(st1,st2,st3,st4,st5,st6); % plot title
title(stitle)
legend('input voltage','output voltage')
axis([0 10 -5 15]); % set axis for voltage range of -5 to 15
34. The SIM Function
Suppose we wish to see how the capacitor voltage changes for
several different values of C. To do this we will use the sim
command.
To use the sim command we must 1st save the model. To do
this select the File Save As menu and save the file as
capacitor_charging_model. Make sure you save the model to a
folder in your MATLAB path.
Next execute the M-File script on the next slide. The for loop
with the sim command runs the model with a different capacitor
value each time the sim command is executed. The output data
is saved as vc(k,:)
The plot command is used to plot the data for the three different
capacitor values. Note the use of string’s to build the plot
legend.
35. M-Code to Run and Plot the Simulation data
' M-File script to plot simulation data '
R = 1; % set R value;
CAP = [1 1/2 1/4]; % set simulation values for C
for k = 1:3
C = CAP(k); % capacitor value for simulation
sim('capacitor_charging_model'); % run simulation
vc(k,:) = yout(:,2); % save capacitor voltage data
end
plot(tout,vc(1,:),tout,vc(2,:),tout,vc(3,:)); % values to plot
xlabel('Time (secs)'); grid;
ylabel('Amplitude (volts)');
st1 = 'R = '
st2 = num2str(R); % convert R value to string
st3 = ' Omega'; % Greek symbol for Ohm
st4 = ', C = ';
st5 = num2str(CAP(1));
st6 = ' F';
sl1 = strcat(st1,st2,st3,st4,st5,st6); % legend 1
st5 = num2str(CAP(2));
36. M-Code to Run and Plot the Simulation data
sl2 = strcat(st1,st2,st3,st4,st5,st6); % legend 2
st5 = num2str(CAP(3));
sl3 = strcat(st1,st2,st3,st4,st5,st6); % legend 3
title('Capacitor Voltage Plot Using SIM')
legend(sl1,sl2,sl3); % plot legend
axis([0 10 -5 15]); % set axis for voltage range of -5 to 15
39. SIM script to run RLC Circuit Model
' M-File script to plot simulation data '
R = 1; % set R value;
L = 1; % set L
CAP = [1/2 1/4 1/8]; % set simulation values for C
for k = 1:3
C = CAP(k); % capacitor value for simulation
sim('RLC_circuit'); % run simulation
vc(k,:) = yout; % save capacitor voltage data
end
plot(tout,vc(1,:),tout,vc(2,:),tout,vc(3,:)); % values to plot
xlabel('Time (secs)'); grid;
ylabel('Amplitude (volts)');
st1 = 'C = ';
st2 = num2str(CAP(1));
st3 = ' F';
sl1 = strcat(st1,st2,st3); % legend 1
st2 = num2str(CAP(2));
sl2 = strcat(st1,st2,st3); % legend 2
st2 = num2str(CAP(3));
sl3 = strcat(st1,st2,st3); % legend 3
40. SIM script to run RLC Circuit Model
st1 ='Capacitor Voltage Plot, R = ';
st2 = num2str(R); st3 = 'Omega';
st4 = ',L = '; st5 = num2str(L);
st6 = ' H';
stitle = strcat(st1,st2,st3,st4,st5,st6);
title(stitle)
legend(sl1,sl2,sl3); % plot legend
axis([0 10 -5 20]); % set axis for voltage range of -5 to 20