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Zvonar and Brady [337] proposed a multiuser detector for synchronous CDMA systems designed for a frequency-selective Rayleigh fading channel Their approach also used a bank of matched filters followed by a so-called whitening filter, but maximal ratio combining was used to combine the resulting signals The decorrelating detector of [336] was further developed for differentially-encoded coherent multiuser detection fading channelsby Zvonar in flat et al [338] Zvonar also amalgamated the decorrelating detector with diversity combining, in order to achieve performance improvements in frequency selective fading channels [339] A multiuser detector jointly performing decorrelating CIR estimation and data detection was investigated by Kawahara and Matsumoto [340] Path-by-path decorrelators were employed for each user in order to obtain the input signals required for CIR estimation and the CIR estimates as well as the outputs of a matched filter bank were fed into a decorrelator for demodulating the data. 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# ... To see the newly applied format, choose View Live View or click the Live View button on the Document toolbar. Each of Dreamweaver s five server models offers slightly different data formats through the Bindings panel. A complete list of all the standard data formats, with relevant examples, is shown in Tables 19-1 (ASP), 19-2 (ColdFusion), and 19-3 (PHP). getAttribute2() asp.net upc-a Barcode UPC-A - CodeProject
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NET UPC-A Generator Controls to generate GS1 UPC-A barcodes in VB. NET , C# applications. Download Free Trial Package | Developer Guide included ... A variant of this idea was also presented by Hosseinian, Fattouche and Sesay [341], where training sequences and a decorrelating scheme were used for determining the CIR estimate matrix This matrixwas then used in a decorrelating decision feedback scheme for obtaining the data estimates Juntti, Aazhang and Lilleberg [342] proposed iterative schemes, in order to reduce the complexity Sung and Chen [343] advocated using a sequential estimator for minimizing the mean square estimation error between the received signal and the signal after detection The cross-correlations between the users spreading codes and the estimates of the channel-impaired received signal of each user were needed, in order to obtain estimates of the transmitted data for each user Duel-Hallen [344] proposed a decorrelating decision-feedback detector for removing the MA1 from a synchronous system communicating over a Gaussian channel. FIGURE 1.11 An adjustment layer. Create new adjustment layers with the New Fill or Adjustment Layer icon. Adjustment layer asp.net upc-a UPC-A Barcode Generator for ASP . NET Web Application
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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 ... The outputs from a bank of filters matched to the spreading codes of the users were passed through a whitening filter This filter was obtained by decomposing the CCL matrix of the users spreading codes with the aid of the Cholesky decomposition [233] technique The results showed that MA1 could be removed from each user s signal successively, assuming that there was no error propagation However, estimates of the received signal strengths of the users were needed, since the users had to be ranked in order of decreasing signal strengths so that the more reliable estimates were obtained first Duel-Hallen s decorrelating decision feedback detector [344] was improved by Wei and Schlegel [345]with the aid of a sub-optimum variant of the Viterbi algorithm, where the most likely paths were retained in the case of merging paths in the Viterbi algorithm. and the overall probability symbol errorof the detector is of given by: The decorrelating decision feedback detector [344] was alsoimproved with the assistance of soft-decision convolutional coding by Hafeez and Stark [346] Soft decisions from a Viterbi channel decoder were fed back into the filter for signal cancellation Having reviewed the range of linear receivers, let us now consider the class of joint detection schemes, which can be found in the family-tree of Figure 124 in the next section.. This step involves both the systematic collection of knowledge about fraud schemes and brainstorming about possible fraud schemes and scenarios that could result from the identi ed fraud risk factors. For example, if a company may nd it dif cult to comply with certain nancial ratios in loan covenants, the brainstorming would desirably include the identi cation and consideration of scenarios and fraud schemes that could be perpetrated to manipulate those ratios. This process desirably involves personnel from different functions and levels in the company, including management, internal audit, business process owners, IT management, legal, HR, risk/compliance and fraud/security, with oversight from the audit committee. Consideration can be given to past frauds and allegations of fraud within the company and the industry. Media searches and databases of reported and alleged frauds can be helpful in identifying fraud risks that could impact the company in the future. As with investment returns, past experience is not necessarily an accurate predictor of future experience. Organized criminal groups experiment with fraud schemes to identify those with the most promise. Then they exploit them, potentially on a much bigger scale, which can cause fraud losses to increase suddenly for the companies targeted. The identi cation of possible fraud and corruption risks would desirably be performed without consideration of the existence or effectiveness of internal controls. This can be a tough exercise, getting to the inherent risk in the company, but separating the assessment of fraud and corruption risks from the assessment of the risk mitigation impact of controls, which follows later, helps to produce a higher quality risk assessment. { =
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