bv_cvxbook_extra_exercises

Remark you might be surprised at both the maximum

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Unformatted text preview: x, given y , taking into account the prior assumption that x is nonnegative and monotonically nondecreasing, as a convex optimization problem. Be sure to indicate what the problem variables are, and what the problem data are. (b) We now consider a specific instance of the problem, with problem data (i.e., N , k , h, and y ) given in the file ml_estim_incr_signal_data.m. (This file contains the true signal xtrue, which of course you cannot use in creating your estimate.) Find the maximum likelihood estimate xml , and plot it, along with the true signal. Also find and plot the maximum likelihood ˆ estimate xml,free not taking into account the signal nonnegativity and monotonicity. ˆ Hint. The function conv (convolution) is overloaded to work with CVX. 6.7 Relaxed and discrete A-optimal experiment design. This problem concerns the A-optimal experiment design problem, described on page 387, with data generated as follows. n = 5; % dimension of parameters to be estimated p = 20; % number of available types of meas...
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