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Speech feature learning is very important for the design of classification algorithm of Parkinson's disease (PD). Existing speech feature learning method for classification of PD just pays attention to the speech feature. This paper proposed a novel hybrid feature learning algorithm which puts the features of all the speech segments of each subject together, thereby obtaining new and high efficient...
Functional magnetic resonance imaging (fMRI) is a powerful tool to analyze brain development and neuronal activity. Identifying discriminative brain regions between various groups within a population has generated great interest in recent years. In this work, we consider the problem of estimating multiple sparse, co-activated brain regions from fMRI observations belonging to different classes. More...
In indoor environment, there are gross errors in random measured values of base station, which has effect on generalization ability of BP neural network and then results in low location accuracy. In order to improve location accuracy, location algorithm of BP Neural Network based on residual analysis is proposed, namely conducting pretreatment on measured values separately in training phase and location...
In this paper, we propose an novel instance selection algorithm and an improved adaptive neuro-fuzzy algorithm for Computer Aided Detection (CAD) of mammography. Firstly, the X-Ray images are partitioned into blocks. Secondly, the texture model is built for all negative packages instances. The distances from the unknown instances to the average model of negative packages are calculated. The instance...
A new efficient algorithm using the compressed domain features of H.264 INTRA frames is proposed for moving object extraction on huge video surveillance archives. To achieve searching efficiency, we propose to locate moving objects by scrutinizing only the INTRA frames in video surveillance archives in H.264 compressed domain with short GOP length. In the proposed structure, a modified codebook algorithm...
An air defense decision-making model based on modern artificial intelligence technology is introduced in this paper. It also solve many difficult problems during model establishing, such as design of neural network structure, network propagation algorithm, fuzzy control algorithm and data reduction algorithm. Simulation experiment with typical battlefield situation data is conducted. First, quantify...
ShanDong Heze International Peony Fair is an important to local development, But peony florescence hardly meets the date of the Fair. How to accurately predict the peony florescence is very urgent. Based on the analysis of the relationship between the peony florescence and the temperature. A prediction model for peony florescence built on the air temperature and soil temperature by BP network. The...
Heze International Peony Fair develops the local economy, But subject to weather conditions, predicting peony florescence hardly meets the actual date. In order to accurate predicting, multiple linear regression analysis and multiple nonlinear regression analysis have been mentioned. The relationship of the factors which impact the peony florescence such as light, temperature and moisture, etc, is...
According to the off-line handwritten Chinese characters, a classification and recognition method which is combined by pruning FSVM coarse classification and SVM fine classification is proposed in this text. First cut no value minor to reduce the number of support vector machines, and then determine the coarse classification through fuzzy membership when the coarse classification is done. In fine...
Tracking-by-detection is an attractive paradigm for intelligent visual surveillance applications where clutter, lighting variations, target overlap and occlusions hamper conventional background modeling. However, state-of-the-art vehicle and pedestrian detectors based on discriminative classification are too computationally expensive for real-time implementation on embedded smart cameras. This paper...
With the evolution of robotic systems to facilitate overground walking rehabilitation, it is important to understand the effect of robotic-aided body-weight supported loading on lower limb muscle activity, if we are to optimize neuromotor recovery. To achieve this objective, we have collected and studied electromyography (EMG) data from key muscles in the lower extremity from healthy subjects walking...
Due to the labor-intensiveness and the shortage of therapists in the application of most forms of manually assisted gait training in neuro-rehabilitation, robotics rehabilitation gait systems have been developed to contribute in such fields of neuro-rehabilitation. This paper presents an overground gait rehabilitation robot, which consists of a pair of robotic orthosis (RO) connected to pelvic arm...
A body-weight support locomotion training (BWSLT) device has been developed for the lower limb rehabilitation. In order to evaluate the effectiveness of the device, seven healthy subjects have participated the walking experiments. The experiments include the walking along a floor mat and the walking with the assistance of the device. On the other hand, experiments have been conducted on one spinal...
As construction Industry is part of the complex non-linear system of the national economic development, the BP neural network of the artificial intelligence can to some extent deal with problems of the complex nonlinear system. Therefore, it has been widely applied to solving macroeconomic problems at present. The paper through systematically integrating econometrics with BP neural network establishes...
The Cognitive Radio (CR) technology enables the unlicensed users to share the spectrum with the licensed users on a non-interfering basis. Spectrum sensing is an important function for the unlicensed users to determine availability of a channel in the licensed user's spectrum. However, spectrum sensing consumes considerable energy which can be reduced by employing predictive methods for discovering...
This paper presented and discussed a new electrochemical analysis method FARSA (frequency and amplitude response spectroscopy analyzing), which can be applied to qualitatively and quantitatively analyze material's properties and concentration with certain methods of chemometrics, and introduced the system and functional structure of FARSA. Principal component analysis (PCA) was used to the identification...
In this paper, a new prediction model, based on chaos theory and BP artificial neural network, is developed to predict the risk of credit card transactions. Embedding dimension of phase-space reconstruction is used to determine network structure, and overcomes the dependence on large amount of samples. Experiments shows that the method based on combination of chaos theory and neural network can improve...
One of key points in developing support vector machine (SVM) is the incorporating prior knowledge of learning task into SVM. A very common type of a prior knowledge is invariance of the input data. The research on incorporating method of invariance and SVM is an important focus for SVM in recent years, and it can help to improve the generalization performance efficiently. This paper describes and...
Identification of sentiment orientation in Chinese words is essential for getting sentiment comprehension of Chinese text, and building a basic semantic lexicon with Chinese emotional words will provide a core subset for identifying emotional words in a special area. It can not only help to identify and enlarge semantic lexicon in corpus effectively but also improve classification efficiency. On the...
Typhoon is one type of disaster weather which can impose serious impact on the life and production of human society. It has special physical characteristics of clouds with the structure of cloud eye, cloud walls and spiral cloud bands. Much information about Typhoon motion, wind field and heavy rainfall is contained in spiral cloud bands. Therefore it is very important to segment and recognize its...
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