Skip to main content

C++ Programming


How to run C++ program on your computer

To run any programming language on your local machine or computer you need a compiler first. The compiler reads each and every line of your program. It interprets line by line actually. If there is no error in the program, they only go ahead to run your particular program. In our case, we are using the "DEV C++" compiler to run our programs. You can easily download and install the "DEV C++ application file" or .exe file from the internet.


How to save C++ files on your computer

You simply go to your "DEV C++" and then click on "new" in the file section in the upper tabs. Then save the file adding the ".cpp" extension. For example, if your program name is "myfirstprogram" then save it as "myfirstprogram. cpp". 


Hello World program in C++

#include <iostream> 
using namespace std;           // it calls the library
int main() {                         // it defines the method main()
cout << "Hello World!";  // 'cout' is used for printing
return 0;                             // it returns only one value
}


Result

Hello World!


In the above program, "using namespace std;" calls a library that has a set of signs that are used to identify and refer to objects of various kinds. Here in the 3rd line main() is a method. 



How To Add Comments in C++ Programming

To add comments in C++ Programming you need to write "//", then write your comment. 

For Example

#include <iostream>

using namespace std;

int main() {

int x = 22; //declaring of variable x

if (x >= 10) {

cout << "It is true";

}

else {

cout << "It is false";

}

/* 

It is a comment on multiple lines

If...else is used for adding conditions in C programming

*/

return 0;

}


Here, in the above code single line comment is written after "//". But if comments contain multiple lines then we use "/* Your Comment of multiple lines */" as shown in the above code.



Declaring of Variable in C++

In all programming languages, we declare some variable for specific purposes.


#include <iostream>

using namespace std;

int main() {

  int x = 5;

  int y = 10;

  int sum = x + y;

  cout << "Value of x + y = " << sum;

}


Result

Value of x + y = 15


Here in the above code, we've declared two variables x = 5, and y=10.



'Else If' Condition in C++ Programming

#include <iostream>

using namespace std;

int main() {

  int product;

  cout << "Enter the number of product: ";

  cin >> product; 

  if (product < 500) {

    cout << "Total price = " << product*20;

  } else if (product >= 500 && product < 1000) {

    cout << "Total price = " << product*18;

  } else {

    cout << "Total price = " << product*15;

  }

  return 0;

}


Result

Enter the number of products: 400

Total price = 8000


We implemented three different conditions for an e-commerce application for the wholesale market in the code above. If you buy less than 500 items, you'll have to pay $20 for each one. If you buy more than 500 but fewer than 1000 units, you pay 18 dollars for each unit. The third condition is that if you purchase more than 1000 items, you will be charged $15 for each item.

 

While For - Loop in C++ Programming


We often need to run a loop inside a program to run several iterations and impose many logics, conditions, etc. 


Example

In a school sport, a group of three pupils will compete in a three-round running race. After each round, you must record the time taken by each student. Calculate the average time taken by each student over the three rounds once they have completed all of the rounds, and choose the student with the lowest average timing as the best runner. If more than one student meets the minimum average timing criteria, they must all be chosen. Show the fastest runner's name and average timing.


Solution in C++

Inputs:

The time taken by three students over three rounds to complete a 100-meter run is as follows

Student A: 8, 9, 9 (in second)

Student B: 9, 8, 12 (in second)

Student C: 7, 11, 9 (in second)

Condition:

All students will be judged unfit if they fail to maintain an average timing of 12 seconds over the three rounds, or if the time average taken by all students is greater than 12 seconds.

The input of the code is below:

8

9

7

9

8

11

9

12

9

Code:

#include <iostream>

#include <cmath>

using namespace std;

int main() {

int x, T1=0, T2=0, T3=0, count=1;

double A1, A2, A3;

while (count <=9)

{

cin >> x;

if(count%3==1)

T1=T1+x;

else if(count%3==2)

T2=T2+x;

else

T3=T3+x;

count++;

}

A1= (T1/3);

A2= (T2/3);

A3= (T3/3); 

if(A1>=12 && A2>=12 && A3>=12) {

cout<<"All trainees are unfit";

return 0;

}

if(A1<=A2 && A1<=A3){

cout<<"Student A"<<endl;

}

if(A2<=A1 && A2<=A3){

cout<<"Student B"<<endl;

}

if(A3<=A1 && A3<=A2){

cout<<"Student C"<<endl;

}

return 0;

}

Result:

Student A


We can say Student A takes less average time to cover 3 rounds of 100 meters runs.


 

Solve the following C Programs

#include<stdio.h>
int main() {
int a=2,b=2;
a=b<<a;
printf("%d", a);
return 0;
}


Output: 8


Explanation:

Operator "<<" denotes the left shifting of bits and operator ">>" denotes the right shifting of bits.

So, here operation occurs in bit level

b = 2 = binary 10; If we shift bits in the left direction by 2 places then it will be 1000 which is equal to decimal 8

So, the output will be 8 in the above code.

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

OFDM Symbols and Subcarriers Explained

This article explains how OFDM (Orthogonal Frequency Division Multiplexing) symbols and subcarriers work. It covers modulation, mapping symbols to subcarriers, subcarrier frequency spacing, IFFT synthesis, cyclic prefix, and transmission. Step 1: Modulation First, modulate the input bitstream. For example, with 16-QAM , each group of 4 bits maps to one QAM symbol. Suppose we generate a sequence of QAM symbols: s0, s1, s2, s3, s4, s5, …, s63 Step 2: Mapping Symbols to Subcarriers Assume N sub = 8 subcarriers. Each OFDM symbol in the frequency domain contains 8 QAM symbols (one per subcarrier): Mapping (example) OFDM symbol 1 → s0, s1, s2, s3, s4, s5, s6, s7 OFDM symbol 2 → s8, s9, s10, s11, s12, s13, s14, s15 … OFDM sym...

Constellation Diagrams of ASK, PSK, and FSK

๐Ÿ“˜ Overview of Energy per Bit (Eb / N0) ๐Ÿงฎ Online Simulator for constellation diagrams of ASK, FSK, and PSK ๐Ÿงฎ Theory behind Constellation Diagrams of ASK, FSK, and PSK ๐Ÿงฎ MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK ๐Ÿ“š Further Reading ๐Ÿ“‚ Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... ๐Ÿงฎ Simulator for constellation diagrams of m-ary PSK ๐Ÿงฎ Simulator for constellation diagrams of m-ary QAM BASK (Binary ASK) Modulation: Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1.    BFSK (Binary FSK) Modulation: Transmits one of two signals: +√Eb​ ( On the y-axis, the phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

๐Ÿ“˜ Overview of BER and SNR ๐Ÿงฎ Online Simulator for BER calculation of m-ary QAM and m-ary PSK ๐Ÿงฎ MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... ๐Ÿ“š Further Reading ๐Ÿ“‚ View Other Topics on M-ary QAM, M-ary PSK, QPSK ... ๐Ÿงฎ Online Simulator for Constellation Diagram of m-ary QAM ๐Ÿงฎ Online Simulator for Constellation Diagram of m-ary PSK ๐Ÿงฎ MATLAB Code for BER calculation of ASK, FSK, and PSK ๐Ÿงฎ MATLAB Code for BER calculation of Alamouti Scheme ๐Ÿงฎ Different approaches to calculate BER vs SNR What is Bit Error Rate (BER)? The abbreviation BER stands for Bit Error Rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. BER = (number of bits received in error) / (total number of tran...

Power Spectral Density Calculation Using FFT in MATLAB

๐Ÿ“˜ Overview ๐Ÿงฎ Steps to calculate the PSD of a signal ๐Ÿงฎ MATLAB Codes ๐Ÿ“š Further Reading Power spectral density (PSD) tells us how the power of a signal is distributed across different frequency components, whereas Fourier Magnitude gives you the amplitude (or strength) of each frequency component in the signal. Steps to calculate the PSD of a signal Firstly, calculate the first Fourier transform (FFT) of a signal Then, calculate the Fourier magnitude of the signal The power spectrum is the square of the Fourier magnitude To calculate power spectrum density (PSD), divide the power spectrum by the total number of samples and the frequency resolution. {Frequency resolution = (sampling frequency / total number of samples)} Sampling frequency (fs): The rate at which the continuous-time signal is sampled (in Hz). ...

Fundamentals of Channel Estimation

Channel Estimation Techniques Channel Estimation is an auto‑regressive process that may be performed with a number of iterations. There are commonly three types of channel estimation approaches: Pilot estimation Blind estimation Semi‑blind estimation. For Channel Estimation, CIR [↗] is used. The amplitudes of the impulses decrease over time and are not correlated. For example: y(n) = h(n) * x(n) + w(n) where y(n) is the received signal, x(n) is the sent signal, and w(n) is the additive white Gaussian noise. At the next stage: h(n+1) = a * h(n) + w(n) The channel coefficient will be modified as stated above at the subsequent stage. The scaling factor “a” determines the impulse’s amplitude, whereas h(n+1) represents the channel coefficient at the following stage. Pilot Estimation Method To understand how a communication medium is currently behaving, a channel estimate is necessary...

Pulse Position Modulation (PPM)

Pulse Position Modulation (PPM) is a type of signal modulation in which M message bits are encoded by transmitting a single pulse within one of 2แดน possible time positions within a fixed time frame. This process is repeated every T seconds , resulting in a data rate of M/T bits per second . PPM is a form of analog modulation where the position of each pulse is varied according to the amplitude of the sampled modulating signal , while the amplitude and width of the pulses remain constant . This means only the timing (position) of the pulse carries the information. PPM is commonly used in optical and wireless communications , especially where multipath interference is minimal or needs to be reduced. Because the information is carried in timing , it's more robust in some noisy environments compared to other modulation schemes. Although PPM can be used for analog signal modulation , it is also used in digital communications where each pulse position represents a symbol or bit...

Theoretical vs. simulated BER vs. SNR for ASK, FSK, and PSK

๐Ÿ“˜ Overview ๐Ÿงฎ Simulator for calculating BER ๐Ÿงฎ MATLAB Codes for calculating theoretical BER ๐Ÿงฎ MATLAB Codes for calculating simulated BER ๐Ÿ“š Further Reading BER vs. SNR denotes how many bits in error are received for a given signal-to-noise ratio, typically measured in dB. Common noise types in wireless systems: 1. Additive White Gaussian Noise (AWGN) 2. Rayleigh Fading AWGN adds random noise; Rayleigh fading attenuates the signal variably. A good SNR helps reduce these effects. Simulator for calculating BER vs SNR for binary ASK, FSK, and PSK Calculate BER for Binary ASK Modulation Enter SNR (dB): Calculate BER Calculate BER for Binary FSK Modulation Enter SNR (dB): Calculate BER Calculate BER for Binary PSK Modulation Enter SNR (dB): Calculate BER BER vs. SNR Curves MATLAB Code for Theoretical BER % The code is written by SalimWireless.Com clc; clear; close all; % SNR v...

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...

๐Ÿงฎ MATLAB Code for BPSK, M-ary PSK, and M-ary QAM Together ๐Ÿงฎ MATLAB Code for M-ary QAM ๐Ÿงฎ MATLAB Code for M-ary PSK ๐Ÿ“š Further Reading MATLAB Script for BER vs. SNR for M-QAM, M-PSK, QPSK, BPSK % Written by Salim Wireless clc; clear; close all; num_symbols = 1e5; snr_db = -20:2:20; psk_orders = [2, 4, 8, 16, 32]; qam_orders = [4, 16, 64, 256]; ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); for i = 1:length(psk_orders) psk_order = psk_orders(i); for j = 1:length(snr_db) data_symbols = randi([0, psk_order-1], 1, num_symbols); modulated_signal = pskmod(data_symbols, psk_order, pi/psk_order); received_signal = awgn(modulated_signal, snr_db(j), 'measured'); demodulated_symbols = pskdemod(received_signal, psk_order, pi/psk_order); ber_psk_results(i, j) = sum(data_symbols ~= demodulated_symbols) / num_symbols; end end for i...