where aiT is the ith row of A, and aiT ⋅ B is a vector–matrix multiplication. Note that fB(aiT):=aiT ⋅ B is a linear function. This property leads to the floating point row checksum test for matrix multiplication. In terms of fB, the row checksum test is: (8.9)fB(Σi=1na...
Proposition (associative property)Matrix multiplication is associative, that is, for any matrices , and such that the above multiplications are meaningfully defined. Proof Other properties Other properties of matrix products are listed here. Transpose of a product PropositionLet be a matrix and a matri...
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The symmetric-convolution multiplication (SCM) property of discrete trigonometric transforms (DTTs) based on unitary transform matrices is developed. Then as the reciprocity of this property, the novel multiplication symmetric-convolution (MSC) property
The condition number of a matrix is an indicator of the sensitivity of the matrix to changes in the result, and is an inherent property of the matrix. Therefore, it is difficult to manually constrain the condition number of the matrix. There are some types of matrices that may have a ...
Intel Community Product Support Forums FPGA FPGA Intellectual Property 6514 Discusiones Floating Point Matrix Multiplication Inscribirse Más acciones Altera_Forum Colaborador Distinguido II 11-18-2009 04:30 PM 2.655 Vistas I want to multiply a 56x56 matri...
Try using BB transpose for AA and AA transpose for BB. Mathmatically, the result = AA * BB = (BB' * AA')'. See http://en.wikipedia.org/wiki/matrix_multiplication#common_properties. Depending on how your matrices are stored, transposes can be "free" in FPGAs. Translate 0...
Returns a string representation of the value of the current instance. (Inherited from NSObject) Unbind(NSString) (Inherited from NSObject) Unbind(String) (Inherited from NSObject) ValueForKey(NSString) Returns the value of the property associated with the specified key. (Inherited from NS...
Try using BB transpose for AA and AA transpose for BB. Mathmatically, the result = AA * BB = (BB' * AA')'. See http://en.wikipedia.org/wiki/matrix_multiplication#common_properties. Depending on how your matrices are stored, transposes can be "free" in FPGAs. Translate 0...
Try using BB transpose for AA and AA transpose for BB. Mathmatically, the result = AA * BB = (BB' * AA')'. See http://en.wikipedia.org/wiki/matrix_multiplication#common_properties. Depending on how your matrices are stored, transposes can be "free" in FPGAs. Translate 0 Kudos ...