A Hadamard Matrix is a square matrix composed of 1 or -1. Using a square matrix system the hadamard matrix could be created
It's matrix C.
Write a program in c++ that take input in a integer matrix of size 4*4 and find out if the entered matrix is diagonal or not.
#include<iostream> #include<vector> #include<random> template<const size_t R, const size_t C> class Matrix { public: using row_type = int[C]; private: // attributes int m_data[R][C]; public: // construction/assignment Matrix (); Matrix (const Matrix& source); Matrix (Matrix&& source); Matrix& operator= (const Matrix<R,C>& source); Matrix& operator= (Matrix<R,C>&& source); ~Matrix () {} public: // accessors row_type& row (const size_t index) { return m_data[index]; } const row_type& row (const size_t index) const { return m_data[index]; } row_type& operator[] (const size_t index) { return m_data[index]; } const row_type& operator[] (const size_t index) const { return m_data[index]; } size_t size() const { return R * C; } size_t rows() const { return R; } size_t cols() const { return C; } public: // operations Matrix<R,C>& operator+= (const Matrix<R,C>&); Matrix<R,C>& operator-= (const Matrix<R,C>&); }; template<const size_t R, const size_t C> Matrix<R,C>::Matrix() { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = 0; } template<const size_t R, const size_t C> Matrix<R,C>::Matrix(const Matrix<R,C>& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = source.m_data[row][col]; } template<const size_t R, const size_t C> Matrix<R,C>::Matrix(Matrix<R,C>&& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = std::move (source.m_data[row][col]); } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator= (const Matrix<R,C>& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = source.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator= (Matrix<R,C>&& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = std::move (source.m_data[row][col]); return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator+= (const Matrix<R,C>& rhs) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] += rhs.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator-= (const Matrix<R,C>& rhs) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] -= rhs.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C> operator+ (const Matrix<R,C>& lhs, const Matrix<R,C>& rhs) { Matrix<R,C> sum (lhs); return sum += rhs; } template<const size_t R, const size_t C> Matrix<R,C> operator- (const Matrix<R,C>& lhs, const Matrix<R,C>& rhs) { Matrix<R,C> sub (lhs); return sub -= rhs; } template<const size_t R, const size_t C, const size_t R1, const size_t C1> Matrix<R,C1> operator* (const Matrix<R,C>& lhs, const Matrix<R1,C1>& rhs) { static_assert (C==R1, "Matrix dimension mismatch!"); Matrix<R,C1> mul; for (size_t x=0; x!=R; ++x) { for (size_t y=0; y!=C1; ++y) { int prod = 0; for (size_t z=0; z!=C; ++z) { prod += lhs[x][z] * rhs[z][y]; } mul[x][y] = prod; } } return mul; } template<const size_t R, const size_t C> std::ostream& operator<< (std::ostream& os, const Matrix<R,C>& m) { for (size_t row=0; row<R; ++row) { for (size_t col=0; col<C; ++col) { std::cout << m[row][col] << '\t'; } std::cout << std::endl; } return os; } int main() { std::default_random_engine generator; std::uniform_int_distribution<int> distribution (1,9); const size_t rows = 2; const size_t cols = 3; Matrix<rows, cols> a, b; for (size_t row=0; row<rows; ++row) { for (size_t col=0; col<cols; ++col) { a[row][col] = distribution (generator); b[row][col] = distribution (generator); } } std::cout << "Matrix a:\n\n" << a << '\n' << std::endl; std::cout << "Matrix b:\n\n" << b << '\n' << std::endl; std::cout << "Matrix a + b:\n\n" << a + b << '\n' << std::endl; std::cout << "Matrix a - b:\n\n" << a - b << '\n' << std::endl; Matrix<cols, rows> c; for (size_t row=0; row<rows; ++row) { for (size_t col=0; col<cols; ++col) { c[col][row] = distribution (generator); } } std::cout << "Matrix c:\n\n" << c << '\n' << std::endl; std::cout << "Matrix a * c:\n\n" << a * c << '\n' << std::endl; }
yes we can do it,in c
using multidimensional array
Hadamard product for a 3 × 3 matrix A with a 3 × 3 matrix B
Jacques Hadamard was born on December 8, 1865.
Jacques Hadamard was born on December 8, 1865.
Jacques Hadamard died on October 17, 1963 at the age of 97.
Jacques Hadamard died on October 17, 1963 at the age of 97.
J. Hadamard has written: 'An essay on the psychology of invention in the mathematical field'
It's matrix C.
Uses similar recursive methods in generation as the standard Walsh/Hadamard matrix, however code entries are of variable length. Specific use is in OSVF code for WCDMA channelization.
int matrix[][]; // the matrix to find the max in int max = matrix[0][0]; int r,c; for(r = 0; r < 3; ++r) { for(c = 0; c < 3; ++c) { if(matrix[r][c] > max) { max = matrix[r][c]; } } } // max is now the maximum number in matrix
Jacques Hadamard was born on December 8, 1865 and died on October 17, 1963. Jacques Hadamard would have been 97 years old at the time of death or 149 years old today.
fu sh|t site
S. S. Agaian has written: 'Hadamard matrices and their applications' -- subject(s): Hadamard matrices