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Example 4.4: Apply the Euclidean algorithm to the numbers A = 112 and B = 54. 112/54 = 2, remainder 4 4 = 112 + ( 2) 54 r1 = r 1 q1r0 r 1 = 112, 54/4 = 13, remainder 2 2 = 54 + ( 13) 4 r 2 = r 0 q2 r 1 r2 = 2 4/2 = 2, remainder 0 Therefore, 2 is the HCF of 112 and 54. A more suitable way of implementing this algorithm is by constructing a table like Table 4.1. The HCF is 2 because the remainder in the next step in the table is 0. In each step of the recursion, it happens that 112 = (1) 112 + (0) 54 54 = (0) 112 + (1) 54 4 = (1) 112 + ( 2) 54 2 = ( 13) 112 + (27) 54 Now Euclidean algorithm is applied to the key equation (X )X 2t + (X )S(X ) = W (X ) The polynomials involved are X 2t and S(X ), and the ith recursion is of the form ri (X ) = si (X )X 2t + ti (X )S(X ) asp.net upc-a UPC-A . NET Control - UPC-A barcode generator with free . NET ...
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6 Apr 2005 ... Demonstrates a method to draw UPC-A barcodes using C#. ... NET 2003 - 7.87 Kb. Image 1 for Drawing UPC-A Barcodes with C# ... Raven, B H (1993) The bases of power: Origins and recent developments Journal of Social Issues, 49, 227 251 Regan, D T (1971) Effects of a favor and liking on compliance Journal of Experimental Social Psychology, 7, 627 639 Rosenbaum, M E (1980) Cooperation and competition In P B Paulus (Ed), The psychology of group in uence (pp 23 41) Hillsdale, NJ: Erlbaum Rotter, J B (1966) Generalized expectancies for internal versus external control of reinforcement Psychological Monographs, 80 (1, Whole No 609) Rudich, E A, & Vallacher, R R (1999) To belong or to selfenhance Motivational bases for choosing interaction partners Personality and Social Psychology Bulletin, 25, 1387 1404 Rusbult, C E, & Martz, J M (1995) Remaining in an abusive relationship: An investment model analysis of nonvoluntary dependence Personality and Social Psychology Bulletin, 21, 558 571 Schachter, S (1959). asp.net upc-a Barcode UPC-A - CodeProject
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The UPC-A Code and the assignment of manufacturer ID numbers is controlled in the ... ASP . NET /Windows Forms/Reporting Services/Compact Framework ... for details on neural network topology and operation. Figure 6.5 provides a basic diagram of a simple neural network. The feedforward nature of the network restricts the network to a single direction of ow and does not allow looping or cycling. The neural network is composed of two or more layers, although most networks consist of three layers: an input layer, a hidden layer, and an output layer. There may be more than one hidden layer, although most networks contain only one, which is suf cient for most purposes. The neural network is connected completely, meaning that every node in a given layer is connected to every node in the next layer, although not to other nodes in the same layer. Each connection between nodes has a weight (e.g., W1A ) associated with it. At initialization, these weights are randomly assigned to values between zero and 1. How does the neural network learn Neural networks represent a supervised learning method, requiring a large training set of complete records, including the target variable. As each observation from the training set is processed through the network, an output value is produced from the output node (assuming that we have only one output node). This output value is then compared to the actual value of the target variable for this training set observation, and the error (actual output) is calculated. This prediction error is analogous to the residuals in regression models. To measure how well the output predictions are tting the actual target values, most neural network models use the sum of squared errors: SSE = The following basic information inequality can be used to prove many of the other inequalities in this chapter. Theorem 17.1.7 (Theorem 2.6.3: Information inequality) two probability mass functions p and q, D(p||q) 0 with equality iff p(x) = q(x) for all x X. Corollary For any two random variables X and Y , I (X; Y ) = D(p(x, y)||p(x)p(y)) 0 (17.11) For any (17.10) or of ces, and the feel, look, and use of the facilities becomes most apparent especially when there is a mismatch.
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