The Contributions Of 19th-Centuary Digital Filter Designers

There are many different types of filters that can be used for decimating, including: cascaded comb-integrator (CIC); direct form polyphase finite impulse response (FIR); half-band FIR; symmetric polyphase FIR filters; transposed direct form II infinite impulse response (IIR) and quasi-linear IIR filters amongst others. As well as using these different configurations, hybrid types can be used for more efficient implementations designed either for better magnitude response, lower power consumptions or

Table 2 illustrates that the second, third and fourth kernel parameter gives the highest accuracy. The performance of the classifier can be evaluated by using Accuracy. The equation (1) can be used to calculate the accuracy. Any of the kernel parameters can be used for further classification to

In the fig1 represents the number of nodes varying with respect to the delay as compared with MILP optimal formulation. It explained our proposed algorithm is better than the MILP formulation.

This algorithm was simulated with Matlab. These datasets and the mentioned characteristics are considered and the algorithm of each dataset with different slopes for the activation fumcion of interest were evaluated so that the best slope can be obtained. After running the program for several times and computing the average to obtain the best result, the optimum slope was evaluated for each dataset and the best slopes for Breast Cancer, Diabetes, Bupa, and

In speech processing, There are various windowing functions, each with different shapes and different characteristics. The form of the window function is not a critical factor. Usually, some soft window like the Von-Hann, rectangular, hanning or hamming window [24] are used to decrease incoherence of the speech signal at the boundaries of each frame segment.

As an overall benefit the Exponential smoothing method should be viewed as the best option for the given situation and hence it should be used for continuing analysis and the decision making process.

The proposed filter is an efficient, high-performance and flexible filter. Because of frequency selective nature of BPF, it is used mainly in reception device for electromagnetic interference reduction. Also the nearer frequency channels are separate out by proper filtering at particular frequency

RBF is relatively adaptive in nature, which is used for classification and pattern reorganization. The performance of the RBF neural network is compared to the commonly used multilayer network model and the classical logistic regression.RBF neural network is based on the supervised learning. This method works independently and based on many researches and is popular alternative to the traditional MLP (Multi Layer Preceptor).RBF neural networks works perfectly in modeling the non linear data and it can be trained in one stage rather than the iterative process as like

A neural network’s accuracy depends on the data provided to the network. In this case, in order

Cross-validation method was used to evaluate the predictive power of models. Dataset was equally divided into two parts. Models were fitted on training set and tested on testing set.

The Fourier Series is only capable of analyzing the frequency components of certain, discretefrequencies (integers) of a given function. In order to study the casewhere the frequency components of the sine and cosineterms are continuous, the concept of the Fourier Transform must be introduced. The imaginary exponential form of the Fourier Transform is defined as

Performance of the algorithm was evaluated using the validation set. We calculated the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy as follows:

The remainder of this paper is structured as follows next section describes the problem formulation, Section-III reviews the related work done. Section IV presents the proposed fuzzy genetic algorithm. In Section V the experiments and results of the previous and this study were analyzed and compared, Section VI presents the conclusions drawn from the proposed modified FGA.

The test of reliability, efficiency and validation of optimization algorithms is frequently carried out by using a chosen set of common standard benchmarks or test functions from the literature. The number of test functions in most papers varied from a few to about two dozens. Ideally, the test functions used should be diverse and unbiased, however, there is no agreed set of test functions in the literature. For any new optimization, it is essential to validate its performance and compare with other existing algorithms over a good set of test functions. A common practice followed by many researches is to compare different algorithms on a large test set, especially when the test involves function optimization. However, it must be noted that

Department of Electrical, Electronic and Systems Engineering Universiti Kebangsaan Malaysia 43600 UKM, Bangi, Selangor, Malaysia