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Hi my name is Claire Tomlin Iamp;#39;m a professor of electrical engineering and computer sciences at Berkeley and this is module 24 in a series that weamp;#39;re recording to support the course eecs 221 a linear system theory at Berkeley in this module weamp;#39;re going to talk about diagonalization of a matrix and how itamp;#39;s used in systems theory how it makes analysis of a system easier so again weamp;#39;re dealing with as weamp;#39;ve talked about in previous modules linear time-invariant systems at this point so in general this is our system X dot is equal to ax plus B you y is equal to CX Plus D you and in terms of solving this equation we know and we know exactly how to write out the solution of the equation so if we have an initial condition X 0 e to the a t minus tau B you at tau D tau okay so thatamp;#39;s the solution so it involves this matrix exponential e to the 80 ok so Iamp;#39;m computing e to the 80 our method for doing that is computing the inverse Lap
