for many years, researchers have studied high accuracy methods for recognizing the handwriting and achieved many significant improvements. however, an issue that has rarely been studied is the speed of these methods. considering the computer hardware limitations, it is necessary for these methods to run in high speed. one of the methods to increase the processing speed is to use the computer pa...

Flash memories are a type of non-volatile memory based on floating-gate transistors. The use of commodity and embedded flash memories are growing rapidly as we enter the system-on-chip (SOC) era. Conventional tests for flash memories are usually ad hoc—the test procedure is developed for a specific design. We propose improved March-like algorithms (i.e., March FT) for both bit-oriented and word...

In this paper we describe a methodology for obtaining modular artificial neural network based control architectures for snake-like robots automatically. This approach is based on the use of behavior modulation structures that are incrementally evolved using macroevolutionary algorithms. The method is suited for problems that can be solved through a progressive increase of the complexity of the ...

We propose a unified framework for making a wide range of PCA-like algorithms – including the standard PCA, sparse PCA and non-negative sparse PCA, etc. – robust when facing a constant fraction of arbitrarily corrupted outliers. Our analysis establishes solid performance guarantees of the proposed framework: its estimation error is upper bounded by a term depending on the intrinsic parameters o...

For most English words, dictionaries give various senses: e.g., “bank” can stand for a financial institution, shore, set, etc. Automatic selection of the sense intended in a given text has crucial importance in many applications of text processing, such as information retrieval or machine translation: e.g., “(my account in the) bank” is to be translated into Spanish as “(mi cuenta en el) banco”...

Perceptron is a classic online algorithm for learning a classification function. In this paper, we provide a novel extension of the perceptron algorithm to the learning to rank problem in information retrieval. We consider popular listwise performance measures such as Normalized Discounted Cumulative Gain (NDCG) and Average Precision (AP). A modern perspective on perceptron for classification i...