Artificial Neural Networks are commonly used in pattern classification, function approximation, optimization, pattern matching, machine learning and associative memories. They are currently being an alternative to traditional statistical methods for mining data sets in order to classify data. Artificial Neural Networks are well-established technology for solving prediction and classification problems, using training and testing data to build a model. However, the success of the networks is highly dependent on the performance of the training process and hence the training algorithm. In this paper, we applied the Artificial Bee Colony (ABC) Optimization Algorithm on training feed-forward neural networks to classify different data sets which are widely used in the machine learning communit...
..., robotic control, signal processing, computer vision and many other problems that fall under the... on the position (solution) in its memory depending on the local information (visual informa...
This paper presents a lossy compression scheme for biomedical images by using a new method. Image data compression using Vector Quantization (VQ) has received a lot of attention because of its simplicity and adaptability. VQ requires the input image to be processed as vectors or blocks of image pixels. The Finite-state vector quantization (FSVQ) is known to give better performance than the memory less vector quantization (VQ). This paper presents a novel combining technique for image compression based on the Hierarchical Finite State Vector Quantization (HFSVQ) and the neural network. The algorithm performs nonlinear restoration of diffraction-limited images concurrently with quantization. The neural network is trained on image pairs consisting of a lossless compression named hierarchic...
... images, like magnetic resonance (MR) and computer tomography (CT) acquired from various modalities, ...
... or doing business, and programs for computers" are excluded from patentability if claimed as suc... significance of the different files in the memory and the way the input data and stored data was pro...
Biofeedback is a treatment technique in which people are trained to improve their physiological functions by using different signals from their own bodies, e.g. from skin, heart (ECG), muscles (EMG), brain (EEG) etc. Psychotherapeutists use it to decrease intrapsychic tension in anxious and depressive patients and epileptics or learn to relax boys who suffered from attention deficit and hyperactivity disorders. The main system for consciousness (thalamocortical reverberation circuit) generates whole brain electromagnetic frequencies permanently (1-30 Hz = EEG activity). But we choose a specific frequency band, e.g. SMR (Sensory Motor Rhythm = 13-18 Hz) and these SMR episodes are rewarded by success in a simultaneously watched TV game. SMR is then repeated still more often and brings int...
...operating conditioning. Learning and memory are two sides of one coin. From the static point o...Copyright Institute of Computer Science 2010Provided by ProQuest LLC. All Rights R...
Associative neural network models are a commonly used methodology when investigating the theory of associative memory in the brain. Comparisons between the mammalian hippocampus and associative memory models of neural networks have been investigated [12]. Biologically based networks are systems built of complex biologically realistic cells with a variety of properties. Here we compare and contrast associative memory function in a network of biologically-based spiking neurons [22] with previously published results for a simple artificial neural network model [11]. We shall focus primarily on the recall process from a memory where patterns have previously been stored by Hebbian learning. We investigate biologically plausible implementations of methods for improving recall under biological...
... created and simulated using the NEURON computer simulation package [5] . Details of the individual...
... von einer Sprache in die andere wohl ein Computer besorgt. Dieses Verfahren kommt heute häufig bei ...Er kooperiert eng mit seinem Translation-Memory-(TM-)Programm. Auf seinem Bildschirm zeichnet sich...
In this paper, the position-only, amplitude-only, and amplitude-phase synthesizes for the shaped-beam patterns of the linear antenna arrays have been achieved by using the clonal selection algorithm (CLONALG). The CLONALG is a relatively novel evolutionary optimization method based on the clonal selection principle of the human immune system. Numerical examples of the pencil, flat-topped, and cosecant patterns are given. Numerical results show that the CLONALG is capable of synthesizing the array patterns with a good performance both in the shaped region and in the sidelobe region.
... techniques and rapid development of computer technologies in recent years have encouraged the r..., the other cloned cells will become memory cells, which are the activated B-cells with high a...
This paper describes an implementation of the Kurtosis and InfoMax algorithms for an independent components analysis in mixed-signal CMOS. Our design uses on-chip calibration techniques and local adaptation to compensate for the effect of device mismatch in arithmetic blocks and analog memory cells. We use our design to perform two-input blind source-separation on mixtures of audio signals and mixtures of EEG signals. Our experiments show that the hardware implementation of InfoMax consistently separates the signals within a normalized reconstruction error of less than 10%, while the reconstruction error of Kurtosis varies between 25% and 60%, due to its higher sensitivity to device mismatch and input statistics. Each circuit has a settling time of 8 µs, occupies a die area of 0.016-0.0...
...Copyright Institute of Computer Science 2009Provided by ProQuest LLC. All Rights R...
Heat generation in the cutting zone occurs as a result of the work done in metal cutting. In this study, in order to measure the temperature generated in the chip-forming zone, numerous experiments were carried out for different cutting regimes. During these experiments, the chip's top temperature was measured using an infrared camera. Collected data were analyzed, and temperature dependence on various cutting regimes was formulated. After that, measured data were modelled using the various techniques: response surface methodology, various types of artificial neural networks and neuro-fuzzy system. The accuracy of the proposed models is presented as well as their suitability for the considered problem. Finally, the system for the adaptive control of the cutting temperature, based on the...
...The images (Fig. 3) are stored in PC memory card, and later analyzed. The maximum cutting temp... in consideration the speed of modern computers, this disadvantage becomes increasingly irrelevant...
The article offers a new view on the organization of the processes of human perception. It introduces the concept of inclusive sensory characteristic, which is a response of a given perceptual level to those features or characteristics of an underlying level whose spatial organization or specific temporal succession constitutes an adaptively meaningful entity. The sequence of inclusive characteristics forms a hierarchy: from features to the highest inclusive characteristics which bind sensory data into unified images and scenes. The highest inclusive characteristic is neither an image nor a scene, but a unique scheme of combination of underlying-level objects, which produces the image or the scene. Specific patterns of electric activity, which map inclusive characteristics, are relayed ...
...A computer simulation of perception confirms that the propose..., high computing power, and large memory. The formation of characteristics which include id...
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