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Exercise 4.15 For the system of eqn. (4.82) with a position measurement y = x: 1. Complete an observability analysis to show that the state of the system is not observable. 2. Analyze the observable and unobservable subspaces to determine the linear combination of states that is not observable. Exercise 4.16 Eqn. (4.125) is derived as in Section 4.6.5. Use similar methods to derive eqns (4.126) and (4.127). Exercise 4.17 Implement a covariance simulation to reproduce the results of Section 4.9.4. 1. Compute and Qd for T = 0.1s. 2. Implement eqn. (4.125) at a 10 Hz update rate. This step will allow the plot of the error standard deviation to show the error growth between measurement updates. 3. For the given value of L, implement eqn. (4.127) at a 1.0 Hz rate. At the measurement instant, store the two values for the covariance. First store the prior value from eqn. (4.125), then store the posterior value from eqn. (4.127). After duplicating the results from Section 4.9.4: 1. Try alternative initial values for the error covariance matrix P. Do they converge to the same steady state conditions 2. Experiment with di erent (stabilizing) gain vectors L to try to improve the state estimation accuracy. Exercise 4.18 Verify that eqn. (4.144) is the solution of eqn. (4.100). 1. Di erentiate P from eqn. (4.144), noting that = F . 2. Add and subtract the term Q to the result of Step 1, then organize the terms that match eqn. (4.100) together. The remaining terms should sum to zero.

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Hard drives store data in a similar fashion to floppy drives, but they typically are not removable and have a different physical structure (see Figure 1-6). A hard drive, also referred to as a fixed drive, consists of one or more hard platters, stacked on top of but not touching one another. The stack of platters is attached through its center to a rotating pole, called a spindle. Each side of each platter can hold data and has its own

Value 1,000 pF /.001 F 1,500 pF /.0015 F 2,000 pF /.002 F 2,200 pF /.0022 F 4,700 pF /.0047 F 5,000 pF /.005 F 5,600 pF /.0056 F 6,800 pF /.0068 F .01 .015 .02 .022 .033

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If you want to change several categories at once, select them by clicking the first category and then z-clicking each of the others. You can also select a range of categories by clicking the first and then SHIFT-clicking the last. Then double-click anywhere in the selection to open the Fonts panel. This trick is useful when you want to change the font family or size of several different categories at once for example, when you grow tired of the Verdana font.

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The information in the parenthesis of the statement is nothing more than a set of field-type pairs. Each field has a SQL data type associated with it, and the list of pairs can be as long as you like.

that Chap l3 focuses linear regression; is hol'r'to deon After a brief review of statistics discussing terminethe "best" straightline througha setof uncertain datapointsBesides quantitativc line we also present how to calculate slopeand intercept this straight the of fbr In we ser'the and visualmethods evaluating validity of the lesults acldition, describe fbr of equations eral approaches the linearization nonlinear andmultiplelinearreglessiou of /4 begins with brief discussions polynomial fit regressirtn cubics,or higher-order Pctlynomial dealswith developinga bc'st clf parabolas which is depolynomialsThis is followed by a clescription multiple linear regression, of variable), is a linear functionof two or more signedtbr the casewhere the dependent exvariables 12, This approach specialutility for evaluating has r1, irrdependent , xtn is on of perimental of datawherethe variable interest dependent a nunlber differentfactors are we how polynomialand multiple regression After multiple regression, illustrate model.

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