http setup the client side

... 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 ... relevant to the open table More of the toolbar buttons are also available The datasheet window shows scroll bars at the right side and in the right side at the bottom To the left of the bottom ... later The status bar at the bottom of the Access window displays the description of the current field included in the table definition For example, if the cursor is in the first field—Order ID—the...

Ngày tải lên: 26/10/2014, 20:39

... 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 ... 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 ... specifies the rows to select sortExpression specifies how the selected rows are to be ordered myDataViewRowState specifies the state of the rows to select You set myDataViewRowState to one of the constants...

Ngày tải lên: 14/12/2013, 13:15

... from the DataViewManager for the table Accessing these properties is identical to accessing the same properties directly through the DataView The RowFilter property of the DataView accesses the ... 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 sample, a filter field is provided on both the Orders ... 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

... unforced dynamical behavior of the system; the subscript k denotes discrete time In other words, the state is the least amount of data on the past behavior of the system that is needed to predict ... (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...

Ngày tải lên: 13/12/2013, 13:15

... then switch to the parallel configuration as the network learns the task Multistream training seems to lessen the need for the series–parallel scheme; the response of the training process to the ... 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 ... annihilate the elements of the submatrix HT P1=2 , thereby yielding k k the left-hand -side matrix Given this result of the square-root filtering procedure, we can perform the network weight update via the...

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 ... hidden layer to predict the next image in the sequence The predicted image is represented at the output layer The prediction error is then used in the EKF equations to update the weights This process ... 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

... comparing the other calculated invariants, it is seen that the Lyapunov exponent and the correlation dimension of the two signals are in close agreement with each other In addition, the Kolmogorov ... for the two signals also match very closely The theoretical horizons of predictability of the two signals are also in agreement with each other These results demonstrate very convincingly that the ... 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...

Ngày tải lên: 14/12/2013, 13:15

... any of the unknown quantities (including the variances, which we will consider in Section 5.4) For the time being, consider only the optimization of fxk gN and w Because the log terms in the above ... 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 ... comparison, the estimates using an EKF with the known neural network model are also shown The MSE for the dual EKF, computed over the final 1000 points of the series, is 0.2171, whereas the EKF produces...

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 ... extended Kalman smoother over the entire sequence using the current parameter estimate Moreover, these expectations are used to re-estimate the parameters, the smoother is then re-run, the parameters ... fantasy data generated from the learned model on the bottom compared it with the known structure of the generating system As the figures show, the algorithm recovers the form of the nonlinear dynamics...

Ngày tải lên: 14/12/2013, 13:15

... divergence of the filter.4 It is these ‘‘flaws’’ that will be addressed in the next section using the UKF 7.3 THE UNSCENTED KALMAN FILTER The UKF addresses the approximation issues of the EKF The state ... As the number of terms in the sum tend to infinity, the residual of the series tends to zero This implies that the series always converges to the true value of the function  If we consider the ... k ¼ These parameters are optimal for the scalar case Table 7.7 summarizes the performance of the different filters The table shows the means and variances of the mean-square error (MSE) of 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

... comparing the other calculated invariants, it is seen that the Lyapunov exponent and the correlation dimension of the two signals are in close agreement with each other In addition, the Kolmogorov ... for the two signals also match very closely The theoretical horizons of predictability of the two signals are also in agreement with each other These results demonstrate very convincingly that the ... 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...

Ngày tải lên: 23/12/2013, 07:16

... any of the unknown quantities (including the variances, which we will consider in Section 5.4) For the time being, consider only the optimization of fxk gN and w Because the log terms in the above ... 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 ... comparison, the estimates using an EKF with the known neural network model are also shown The MSE for the dual EKF, computed over the final 1000 points of the series, is 0.2171, whereas the EKF produces...

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 ... extended Kalman smoother over the entire sequence using the current parameter estimate Moreover, these expectations are used to re-estimate the parameters, the smoother is then re-run, the parameters ... fantasy data generated from the learned model on the bottom compared it with the known structure of the generating system As the figures show, the algorithm recovers the form of the nonlinear dynamics...

Ngày tải lên: 23/12/2013, 07:16

... divergence of the filter.4 It is these ‘‘flaws’’ that will be addressed in the next section using the UKF 7.3 THE UNSCENTED KALMAN FILTER The UKF addresses the approximation issues of the EKF The state ... As the number of terms in the sum tend to infinity, the residual of the series tends to zero This implies that the series always converges to the true value of the function  If we consider the ... k ¼ These parameters are optimal for the scalar case Table 7.7 summarizes the performance of the different filters The table shows the means and variances of the mean-square error (MSE) of the...

Ngày tải lên: 23/12/2013, 07:16

... on basic Kalman 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 ... recording or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher Requests to the Publisher ... a refined estimation of the state xi xii PREFACE  Chapter studies yet another novel idea – the unscented Kalman filter – the performance of which is superior to that of the extended Kalman filter...

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 ... to refresh the list, refresh the first record in the list for the text boxes, and toggle the text boxes so that the user knows he can't edit them Listing 1.14 frmHowTo1_5.vb: Deleting the Selected ... to True, the dataset is set for adding a record with the AddNew method of the BindingContext, and the text boxes are enabled for editing If the user then clicks the btnSave button, the data is...

Ngày tải lên: 21/01/2014, 12:20