In this thesis, a method for signal classification has been developed and implemented on the platform of Matlab and Libsvm, which combines the techniques of wavelet analysis and support vector machine. The whole process is divided into three stages i.e. Signal Generation, Feature Extraction and Classification. There are 6 types of modulated signals i.e. BPSK, QPSK, FSK, ASK, 4ASK and QAM genera...

Extensive research efforts in the area of Information Retrieval were concentrated on developing retrieval systems related to Arabic language for the different natural language and information retrieval methodologies. However, little effort was conducted in those areas for knowledge extraction from the Holly Muslim book, the Quran. In this paper, we present an approach (MQVC) for retrieving the ...

In many datasets, the samples are related by a known image transformation, such as rotation, or a repeatable non-rigid deformation. This applies to both datasets with the same objects under different viewpoints, and datasets augmented with virtual samples. Such datasets possess a high degree of redundancy, because geometrically-induced transformations should preserve intrinsic properties of the...

We introduce iSVM an incremental algorithm that achieves high speed in training support vector machines (SVMs) on large datasets. In the common decomposition framework, iSVM starts with a minimum working set (WS), and then iteratively selects one training example to update the WS in each optimization loop. iSVM employs a two-stage strategy in processing the training data. In the first stage, th...

The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior ...

DNA-binding proteins play pivotal roles in alternative splicing, RNA editing, methylating and many other biological functions for both eukaryotic and prokaryotic proteomes. Predicting the functions of these proteins from primary amino acids sequences is becoming one of the major challenges in functional annotations of genomes. Traditional prediction methods often devote themselves to extracting...

Multi-class classification is one of the major challenges in machine learning and an ongoing research issue. Classification algorithms are generally binary, but they must be extended to multi-class problems for real-world application. more complex than binary classification. In classification, only decision boundaries class known, whereas multiclass several involved. The objective this investig...

Sürekli gelişen şehirler, nüfus artışı ve iklimsel koşullar gibi ekosistem de meydana gelen olumsuz etkenler ile arazi kullanımı değişime uğramaktadır. Uzaktan algılama uyduları tarafından üretilen veriler, yeryüzü araştırmalarda önemli bir rol oynamaktadır. Arazi örtüsü/kullanımı haritaları bu veriler kullanılarak hazırlanmaktadır. örtüsü haritaları, su biyokimyasal döngüler, enerji değişimler...

Mısır, dünyanın birçok yerinde temel gıda olarak kullanılmaktadır. yağ ve yüksek fruktozlu mısır şurubu yapmak için kullanılabilecek iyi bir nişasta kaynağıdır. Mısır unu çok hayati ürünler olduğundan, Yanık, Pas Gri Yaprak Lekesi gibi bazı hastalıkların erken teşhisiyle bitkilerin iyileştirilmesini sağlanarak ürün kalitesinin düşmesi önlenebilecektir. Bu sayede hem ürünün kalitesi de elde edil...

Many researchers adopt Local Binary Pattern for pattern analysis. However, the long histogram created by Local Binary Pattern is not suitable for large-scale facial database. This paper presents a simple facial pattern descriptor for facial expression recognition. Local pattern is computed based on local gradient flow from one side to another side through the center pixel in a 3x3 pixels region...