managing the exchange server hierarchy and core components

... move either one, click the move handle located at the farleft edge of the bar (it looks like a stack of dots) Then, drag the bar away from the top of the window to another edge or leave it in the ... click the command or type the letter underlined in the name of the command If the command shows a right arrow, such as View in Figure 1-5, it’s a submenu Rest the pointer on the item to open the ... resting the mouse pointer on the button in the command bar The Views drop-down list includes the following options: • Large Icons Displays the names of the files and subfolders located in the folder...

Ngày tải lên: 26/10/2014, 20:39

... performed steps and and retrieved the rows from the Order Details table into a DataTable object named orderDetailsDataTable, then the following example retrieves the DataRow with an OrderID and ProductID ... Notice that the Find() method is called through the Rows property of productsDataTable The Rows property returns an object of the DataRowCollection class If the primary key for the database ... from the previous examples, the filter and sort expressions are similar to WHERE and ORDER BY clauses in a SELECT statement You can therefore use very powerful expressions in your calls to the...

Ngày tải lên: 14/12/2013, 13:15

... property of the DataView accesses the expression that filters the view The Sort property of the DataView sorts the view on a single or multiple columns in either ascending or descending order In the ... both the Orders and Order Details table (the Country and EmployeeID fields, respectively) Additionally, the sample allows the data grid to be optionally sorted on the ContactName column The filter ... employeeIdFilter; // Bind the DataViewManager to the grid dataGrid.SetDataBinding(dvm, CUSTOMERS_TABLE); } Discussion The DataView filters and sorts the data in DataTable objects in the DataSet The DataViewManager...

Ngày tải lên: 24/12/2013, 05:15

... (ii) if the optimal estimate xk is restricted to be a linear function of the observables and the cost function is the mean-square error, ^ (iii) then the optimum estimate xk , given the observables ... y1 , y2 ; ; yk , is the orthogonal projection of xk on the space spanned by these observables 5 1.3 KALMAN FILTER With these two theorems at hand, the derivation of the Kalman filter follows ... starts at the final time N and runs backwards Let x fk and ^k xb denote the state estimates obtained from the forward and backward recursions, respectively Given these two estimates, the next issue...

Ngày tải lên: 13/12/2013, 13:15

... propagation to the computation of the total derivative matrix for the ith node; the vector ui;j is the vector of inputs to the ith node at the jth step of k backpropagation; and ci;j is the vector ... two steps, comprising the forward- and backpropagation operations, will depend on whether or not the network being trained has recurrent connections On the other hand, the EKF calculations encoded ... independent of the chosen number of streams On the other hand, we noted above the increase in size for the derivative matrices Hik: l , as well as of the Kalman gain matrices Kik: l However, the computation...

Ngày tải lên: 14/12/2013, 13:15

... in the complexity of the learning task However, since the number of weights in the network is limited and remains the same as in the other experiments, the network cannot simply memorize the ... during testing, the order of the sequences was varied and the network was asked to predict the correct shape and location of the next image in the sequence The complexity of the problem was increased ... so that the network would not learn the order of presentation of the sequences The network was therefore expected to learn the motions associated with each of the three shapes, and not the order...

Ngày tải lên: 14/12/2013, 13:15

... using the first 5000 samples in the same fashion as in the noise-free case The right-hand plots of Figures 4.9a and 4.9b show the attractors of the autonomously generated Ikeda series produced by the ... of the dynamic invariants of the noisy and reconstructed signals in Table 4.5 reveals that the reconstructed signals and their invariants are reasonably close to the noise-free signal and the ... cos½mðkފg; ð4:6Þ where x1 and x2 are the real and imaginary components, respectively, of x and the parameter m is carefully chosen to be 0.7 so that the produced behavior is chaotic The initial values...

Ngày tải lên: 14/12/2013, 13:15

... weighted MSE cost The innovations covariance E½rk rT Š ¼ Rr , on the k k other hand, affects the convergence rate and tracking performance Roughly speaking, the larger the covariance, the more quickly ... ð5:63Þ ^ where xkjN and pkjN are defined as the conditional mean and variance of xk ^ ^ kjN given w and all the data, fyk gN The terms xÀ and pÀ are the conditional kjN mean and variance of xÀ ... nonlinear observation on wk The EKF can then be applied directly, with the equations given in Table 5.2 In the linear case, the relationship between the Kalman filter (KF) and the popular recursive...

Ngày tải lên: 14/12/2013, 13:15

... the observations=inputs and the parameter values The M-step involves system identification using the state estimates from the smoother Therefore, at the heart of the EM learning procedure is the ... outputs, and the conditional distributions over the hidden states For the model we have described, the parameters define the nonlinearities f and g, and the noise covariances Q and R (as well as the ... by picking randomly the values of the nodes that have no parents It then picks randomly the values of their children Stationarity means here that neither f nor the covariance of the noise process...

Ngày tải lên: 14/12/2013, 13:15

... the strike price, while the date in which the option lapses is often referred to as the maturity time Put options, on the other hand, allow the holder to sell the underlying cash product In their ... that the true posterior mean and the mean calculated by the UT agrees exactly to the third order and that errors are only introduced in the first and higherorder terms The magnitudes of these ... position and velocity, and top and _ _ _ bottom pendulum angle and angular velocity, x ¼ ½x; x; y1 ; y1 ; y2 ; y2 Š The system parameters correspond to the length and mass of each pendulum, and the...

Ngày tải lên: 14/12/2013, 13:15

... specify the version of the data to retrieve as one of the DataRowVersion enumeration values: Current, Default, Original, or Proposed Similarly, the GetParentRow( ) method of a row in the child ... result.ToString( ); Discussion The GetChildRows( ) method of a row in the parent table returns the child rows as an array of DataRow objects for a specified DataRelation The method takes an optional ... Environment.NewLine); // Iterate over the OrderDetails records for the Order foreach(DataRow row in orderTable.Rows[i].GetChildRows(ORDERS_ORDERDETAILS_RELATION)) { // Display data for the OrderDetails record...

Ngày tải lên: 14/12/2013, 18:16

... using the first 5000 samples in the same fashion as in the noise-free case The right-hand plots of Figures 4.9a and 4.9b show the attractors of the autonomously generated Ikeda series produced by the ... of the dynamic invariants of the noisy and reconstructed signals in Table 4.5 reveals that the reconstructed signals and their invariants are reasonably close to the noise-free signal and the ... cos½mðkފg; ð4:6Þ where x1 and x2 are the real and imaginary components, respectively, of x and the parameter m is carefully chosen to be 0.7 so that the produced behavior is chaotic The initial values...

Ngày tải lên: 23/12/2013, 07:16

... weighted MSE cost The innovations covariance E½rk rT Š ¼ Rr , on the k k other hand, affects the convergence rate and tracking performance Roughly speaking, the larger the covariance, the more quickly ... ð5:63Þ ^ where xkjN and pkjN are defined as the conditional mean and variance of xk ^ ^ kjN given w and all the data, fyk gN The terms xÀ and pÀ are the conditional kjN mean and variance of xÀ ... nonlinear observation on wk The EKF can then be applied directly, with the equations given in Table 5.2 In the linear case, the relationship between the Kalman filter (KF) and the popular recursive...

Ngày tải lên: 23/12/2013, 07:16

... the observations=inputs and the parameter values The M-step involves system identification using the state estimates from the smoother Therefore, at the heart of the EM learning procedure is the ... outputs, and the conditional distributions over the hidden states For the model we have described, the parameters define the nonlinearities f and g, and the noise covariances Q and R (as well as the ... by picking randomly the values of the nodes that have no parents It then picks randomly the values of their children Stationarity means here that neither f nor the covariance of the noise process...

Ngày tải lên: 23/12/2013, 07:16

... the strike price, while the date in which the option lapses is often referred to as the maturity time Put options, on the other hand, allow the holder to sell the underlying cash product In their ... that the true posterior mean and the mean calculated by the UT agrees exactly to the third order and that errors are only introduced in the first and higherorder terms The magnitudes of these ... position and velocity, and top and _ _ _ bottom pendulum angle and angular velocity, x ¼ ½x; x; y1 ; y1 ; y2 ; y2 Š The system parameters correspond to the length and mass of each pendulum, and the...

Ngày tải lên: 23/12/2013, 07:16

... filter theory, the Rauch–Tung–Striebel smoother, and the extended Kalman filter  Chapter presents the theoretical basis of a powerful learning algorithm for the training of feedforward and recurrent ... Cherkassky and Mulier = LEARNING FROM DATA: Concepts, Theory, and Methods Diamantaras and Kung = PRINCIPAL COMPONENT NEURAL NETWORKS: Theory and Applications Haykin = KALMAN FILTERING AND NEURAL ... Required to Fit the RBFs = 215 References = 216 The Unscented Kalman Filter 221 Eric A Wan and Rudolph van der Merwe Introduction = 221 Optimal Recursive Estimation and the EKF = 224 The Unscented...

Ngày tải lên: 23/12/2013, 07:16

... called When the user clicks the btnDelete button, the record is deleted from the recordset and then from the server The list box is reloaded and the first record in the list is displayed in the text ... data is updated to the dataset and then back to the server If the user clicks the btnCancel button, the edits are canceled In both cases, the mbAddNew variable is set to False and the ActivateEditing ... command against the dataset, deleting the actual rows in the data set The AcceptChanges method is called to send the changes to the dataset, a delete in this case, back to the server Finally, the...

Ngày tải lên: 21/01/2014, 12:20