Modeling and learning continuous-valued stochastic processes with
... Furthermore, if A0 is equivalent to A and C 0 is blended from A0 via the same membership functions (a )a2E , then the process distribution described by C 0 is the same as the one described by C . Finally, if the discrete-valued process described by A is stationary, then the continuous-valued proces ...
... Furthermore, if A0 is equivalent to A and C 0 is blended from A0 via the same membership functions (a )a2E , then the process distribution described by C 0 is the same as the one described by C . Finally, if the discrete-valued process described by A is stationary, then the continuous-valued proces ...
On a quadratic matrix equation associated with an M
... So, (δI − Q)e > 0 for any δ > 0. By Theorem 1.1, δI − Q is a nonsingular M -matrix and thus −Q is an M -matrix. Therefore, equations (2) and (3) are just special cases of the matrix equation (1). We always assume that the matrices E and F are of size at least 2 × 2 and that F 6= 0. If E = 0 then the ...
... So, (δI − Q)e > 0 for any δ > 0. By Theorem 1.1, δI − Q is a nonsingular M -matrix and thus −Q is an M -matrix. Therefore, equations (2) and (3) are just special cases of the matrix equation (1). We always assume that the matrices E and F are of size at least 2 × 2 and that F 6= 0. If E = 0 then the ...
