In this paper protraction movement, namely stepping ahead, of a three joint robot leg is optimized for energy efficiency for any given pair of initial-final tip point positions. For the optimization a modified version...
In this paper protraction movement, namely stepping ahead, of a three joint robot leg is optimized for energy efficiency for any given pair of initial-final tip point positions. For the optimization a modified version of gradient descent based optimal control algorithm with Hamiltonian formulation is used. The objective function is modified in steps to jump over the infeasible and inefficient local optimums. The results of 79 optimizations are used to construct a radial basis function neural network (RBFNN) in order to interpolate between the optimized trajectories. The results are presented and discussed in the paper.
In this paper, four individual approaches to region classification for knowledge-assisted semantic image analysis are presented and comparatively evaluated. All of the examined approaches realize knowledge-assisted an...
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In this paper, four individual approaches to region classification for knowledge-assisted semantic image analysis are presented and comparatively evaluated. All of the examined approaches realize knowledge-assisted analysis via implicit knowledge acquisition, i.e. are based on machine learning techniques such as support vector machines (SVMs), self organizing maps (SOMs), genetic algorithm (GA)and particle swarm optimization (PSO). Under all examined approaches, each image is initially segmented and suitable low-level descriptors are extracted for every resulting segment. Then, each of the aforementioned classifiers is applied to associate every region with a predefined high-level semantic concept. An appropriate evaluation framework has been employed for the comparative evaluation of the above algorithms under varying experimental conditions.
Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on...
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Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on different aspects of visual processing in the cortex, a comprehensive computational model of visual cortex is still missing. We have implemented a computational model of object recognition in ventral visual pathway in our previous work. This hierarchical model covers visual areas V1/V2, V4/PIT, and AIT sending inputs to the Prefrontal Cortex (PFC) for categorization. To extend our model, in this work, we have added a simple model of motion detection in neurons of areas V1 and MT of the dorsal stream to our previous model. This has enabled the model to perform another principal function of the visual cortex, i.e., motion perception.
An overview of digital enhancement techniques for analog circuits is presented. Recent research suggests that the high density and low energy of digital circuits can be leveraged to enable a new generation of interfac...
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An overview of digital enhancement techniques for analog circuits is presented. Recent research suggests that the high density and low energy of digital circuits can be leveraged to enable a new generation of interface electronics that is based on minimal precision, low complexity analog blocks. Today, examples of enhancement schemes can be found in diverse applications and include nonlinearity compensation of ADCs, predistortion of power amplifiers and mismatch calibration in radio receivers. Since it is often difficult to identify commonalities among these different, but conceptually related schemes, this tutorial paper aims to provide a unified and system-oriented perspective of the field.
technology advances have made possible the visualization of electron temperature profiles and fluctuations inside the core of high temperature plasmas via a twodimensional passive millimeter wave imaging system. The e...
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ISBN:
(纸本)1424407494
technology advances have made possible the visualization of electron temperature profiles and fluctuations inside the core of high temperature plasmas via a twodimensional passive millimeter wave imaging system. The electron cyclotron emission imaging (ECEI) system concept and configuration are briefly described. Advanced technologies such as frequency selective surfaces band-stop filter, planar Schottky diode mixer arrays, wide bandwidth IF electronics, and imaging optics are presented.
This paper proposes a practical receiver cancellation technique for removing nonlinear power amplifier (PA) distortion in OFDM systems. By performing the estimation of the PA model parameters at the receiver, the impl...
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This paper proposes a practical receiver cancellation technique for removing nonlinear power amplifier (PA) distortion in OFDM systems. By performing the estimation of the PA model parameters at the receiver, the implementation complexity of the transmitter can be reduced. Furthermore, a simple adaptation rule is provided to enable tracking of the PA model parameters. As a consequence, cancellation of nonlinear distortion can be achieved without assuming that the PA model is known a priori at the receiver. Simulation results show that good levels of distortion cancellation are possible for a system with a broadband PA with memory.
This paper proposes a novel split predistorter structure to remove nonlinear distortion caused by nonlinear power amplifier with memory. Unlike conventional techniques, the new technique does not require an estimation...
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This paper proposes a novel split predistorter structure to remove nonlinear distortion caused by nonlinear power amplifier with memory. Unlike conventional techniques, the new technique does not require an estimation of the memory model at the transmitter leading to a reduced implementation complexity. Simulations have been carried out using the SUI3 channel model developed for IEEE802.16 standard. The results verify the good performance of the proposed predistorter for several relevant power amplifier models.
Feature selection (FS) is a most important step which can affect the performance of pattern recognition system. This paper presents a novel feature selection method that is based on ant colony optimization (ACO). ACO ...
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Feature selection (FS) is a most important step which can affect the performance of pattern recognition system. This paper presents a novel feature selection method that is based on ant colony optimization (ACO). ACO algorithm is inspired of ant's social behavior in their search for the shortest paths to food sources. In the proposed algorithm, classifier performance and the length of selected feature vector are adopted as heuristic information for ACO. So, we can select the optimal feature subset without the priori knowledge of features. Simulation results on face recognition system and ORL database show the superiority of the proposed algorithm
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