what is the disadvantage of sparse matrix?
It hold less information. since majority of it entries are zero's
A fast-transpose is a computer algorithm that quickly transposes a sparse matrix using a relatively small amount of memory. Using arrays normally to record a sparse matrix uses up a lot of memory since many of the matrix's values are zero. In addition, using the normal transpose algorithm to transpose this matrix will take O(cols*elements) amount of time. The fast-transpose algorithm only uses a little memory to record the matrix and takes only O(cols+elements) amount of time, which is efficient considering the number of elements equals cols*rows.
A Hadamard Matrix is a square matrix composed of 1 or -1. Using a square matrix system the hadamard matrix could be created
using multidimensional array
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Yes but why.
A fast-transpose is a computer algorithm that quickly transposes a sparse matrix using a relatively small amount of memory. Using arrays normally to record a sparse matrix uses up a lot of memory since many of the matrix's values are zero. In addition, using the normal transpose algorithm to transpose this matrix will take O(cols*elements) amount of time. The fast-transpose algorithm only uses a little memory to record the matrix and takes only O(cols+elements) amount of time, which is efficient considering the number of elements equals cols*rows.
A sparse matrix contains many (often mostly) zero entries. The basic idea when storing sparse matrices is to only store the non-zero entries as opposed to storing all entries. Depending on the number and distribution of the non-zero entries, different data structures can be used and yield huge savings in memory when compared to a naïve approach. One example of such a sparse matrix format is the (old) Yale Sparse Matrix Format [1]. It stores an initial sparse N×N matrix M in row form using three arrays, A, IA, JA. NZ denotes the number of nonzero entries in matrix M. The array Athen is of length NZ and holds all nonzero entries of M. The array IA stores at IA(i) the position of the first element of row i in the sparse array A. The length of row i is determined by IA(i+1) - IA(i). Therefore IA needs to be of length N + 1. In array JA, the column index of the element A(j) is stored. JA is of length NZ. Another possibility is to use quadtrees
Using sparse matrices to store data that contains a large number of zero-valued elements can both save a significant amount of memory and speed up the processing of that data. sparse is an attribute that you can assign to any two-dimensional MATLAB matrix that is composed of double or logical elements.The sparse attribute allows MATLAB to:Store only the nonzero elements of the matrix, together with their indices.Reduce computation time by eliminating operations on zero elements.For full matrices, MATLAB stores every matrix element internally. Zero-valued elements require the same amount of storage space as any other matrix element. For sparse matrices, however, MATLAB stores only the nonzero elements and their indices. For large matrices with a high percentage of zero-valued elements, this scheme significantly reduces the amount of memory required for data storage.
Example sentence - The grass in the pasture looked sparse.
Slim Pickins had sparse facial hair. Some parts of the desert have sparse growth.
Advantages are that you can see the arc lengths disadvantages some times it doesn't work because of insufficient vertices's or arcs.
It does last as long as a solid structure; weaker but can still hold weight.
The forest was sparse, with few trees scattered across the open landscape.
easy to read helps define the overall structure of the piece
Some disadvantages of using a template include lack of originality, limitations on customization, potential for others to have similar designs, and difficulty in making extensive changes to the layout or structure.
Sparse refers to something that is thinly scattered or distributed. In mathematics and computer science, sparse data or matrices contain mostly zero values, making them more efficient to store and process using specialized algorithms.
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