A BP-based algorithm with 2-dimensional classified normalized correction is developed to reduce the complexity and improve the performance of decoding algorithm for the low density parity check (LDPC) codes. The algorithm first utilizes classification according to the absolute values of incoming messages in check nodes. Then it uses 2-dimensional normalization to correct the minimum and sub-min...

In this paper, a combined normalized and offset min-sum algorithm (NOMSA) is proposed for decoding irregular Low-Density Parity Check (LDPC) codes. The proposed algorithm focuses on improving the decoding performance by avoiding the loss of sign bit information associated with an output reliability value. Also, the proposed algorithm is made suitable for low complexity hardware implementation b...

Normalized Equation and Decomposition Analysis: Computation and Inference This paper joins discussions on normalized regression and decomposition equations in devising a simple and general algorithm for obtaining the normalized regression and applying it to the Oaxaca decomposition. This resolves the invariance problem in the detailed Oaxaca decomposition. An algorithm to calculate an asymptoti...

The principal issue in acoustic echo cancellation (AEC) is to estimate the impulse response between loudspeaker and microphone of a hands-free communication device. This application can be addressed as system identification problem, which solved by using an adaptive filter. most common one for AEC normalized least-mean-square (NLMS) algorithm. It known that overall performance this algorithm co...

We present a set of clustering algorithms that identify cluster boundaries by searching for a hyperplanar gap in unlabeled data sets. It turns out that the Normalized Cuts algorithm of Shi and Malik [1], originally presented as a graph-theoretic algorithm, can be interpreted as such an algorithm. Viewing Normalized Cuts under this light reveals that it pays more attention to points away from th...

Many researchers have controlled and analyzed biped robots that walk in the sagittal plane. Nevertheless, walking robots require the capability to walk merely laterally, when they are faced with the obstacles such as a wall. In walking robot field, both nonlinearity of the dynamic equations and also having a tracking system cause an effective control has to be utilized to address these problems...

This paper presents an efficient design of Adaptive filters which uses enhanced NLMS algorithm for eliminating noise added by mean of various communication media or any other noise sources. By using the appropriate weights, Adaptive filter estimates and remove the estimated noise signal from the available information. LMS and Normalized LMS are two most efficient algorithm for noise cancelation...

Stochastic complexity of a data set is defined as the shortest possible code length for the data obtainable by using some fixed set of models. This measure is of great theoretical and practical importance as a tool for tasks such as model selection or data clustering. In the case of multinomial data, computing the modern version of stochastic complexity, defined as the Normalized Maximum Likeli...

A common model for computing the similarity of two strings X and Y of lengths m, and n respectively with m n, is to transform X into Y through a sequence of three types of edit operations: insertion, deletion, and substitution. The model assumes a given cost function which assigns a non-negative real weight to each edit operation. The amortized weight for a given edit sequence is the ratio of i...

We investigate the convergence behavior of the normalized least mean square (NLMS) algorithm in the structure of a linear transversal filter. At the n-th iteration, the traditional NLMS transversal filter generates the n-th output signal by using linear convolution of the n-th input vector and the n-th coefficient vector. Based on this result, the n-th coefficient vector is updated to the n + 1...