Download PDF by R. Miller, L. Boxer: Algorithms - Sequential, Parallel - A Unified Appr.

By R. Miller, L. Boxer

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In [25], authors proposed an effective ANN-based approach for cardiac arrhythmia classification. 67 % for modular neural network model, generalized feedforward neural network model, and multilayer perceptron model, respectively (Table 2). 4 Conclusion Cardiac arrhythmias are the irregular rhythm of the heart show a serious medical problem sometimes threatening the life. Detection of arrhythmia is an important task in effective management of the disease. Automated system for arrhythmia detection helps the physicians in simplifying the task.

Step 14: Perform Step 5 again. Step 15: Calculate the final fitness value (DP) from Eq. 1). Also, search for global best. Step 16: Check for maximum number of iterations, and if exceeded, print global best and stop; otherwise, go back to Step 3. 5 Test System A standard 16-bus test system is chosen for the application of proposed method. The system diagram is shown in Fig. 2. The system data for the chosen 16-bus test system are tabulated in Table 1. This system operates with tie switches that are open in normal conditions [16–18].

C. S. Lim, AC voltage and current sensorless control of three-phase PWM rectifiers. IEEE Trans. Power Electron. 17(6), 883–890 (2002) 16. W. -C. V. Stanke, Analysis and realization of a pulsewidth modulator based on voltage space vector. IEEE Trans. Ind. Appl. 24(1) (1988) 17. K. Smedley, S. Cuk, One cycle control of power converters. IEEE Trans. Power Electron, 10(6), 625–633 (1995) 18. Y. M. Smedley, One-cycle-controlled three-phase grid connected inverters and their parallel operation. IEEE Trans.

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Algorithms - Sequential, Parallel - A Unified Appr. by R. Miller, L. Boxer

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