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991.
Adaptive Output Feedback Control of Flexible-Joint Robots Using Neural Networks: Dynamic Surface Design Approach 总被引:1,自引:0,他引:1
Sung Jin Yoo Jin Bae Park Yoon Ho Choi 《Neural Networks, IEEE Transactions on》2008,19(10):1712-1726
In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances. 相似文献
992.
Yifeng Zhu Hong Jiang Jun Wang Feng Xian 《Parallel and Distributed Systems, IEEE Transactions on》2008,19(6):750-763
An efficient and distributed scheme for file mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers. This paper presents a novel technique called Hierarchical Bloom Filter Arrays (HBA) to map filenames to the metadata servers holding their metadata. Two levels of probabilistic arrays, namely, the Bloom filter arrays with different levels of accuracies, are used on each metadata server. One array, with lower accuracy and representing the distribution of the entire metadata, trades accuracy for significantly reduced memory overhead, whereas the other array, with higher accuracy, caches partial distribution information and exploits the temporal locality of file access patterns. Both arrays are replicated to all metadata servers to support fast local lookups. We evaluate HBA through extensive trace-driven simulations and implementation in Linux. Simulation results show our HBA design to be highly effective and efficient in improving the performance and scalability of file systems in clusters with 1,000 to 10,000 nodes (or superclusters) and with the amount of data in the petabyte scale or higher. Our implementation indicates that HBA can reduce the metadata operation time of a single-metadata-server architecture by a factor of up to 43.9 when the system is configured with 16 metadata servers. 相似文献
993.
994.
Codevelopmental learning between human and humanoid robot using a dynamic neural-network model. 总被引:1,自引:0,他引:1
Jun Tani Ryu Nishimoto Jun Namikawa Masato Ito 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2008,38(1):43-59
This paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural-network model, which is inspired by human parietal cortex functions. A humanoid robot, with a recurrent neural network that has a hierarchical structure, learns to manipulate objects. Robots learn tasks in repeated self-trials with the assistance of human interaction, which provides physical guidance until the tasks are mastered and learning is consolidated within the neural networks. Experimental results and the analyses showed the following: 1) codevelopmental shaping of task behaviors stems from interactions between the robot and a tutor; 2) dynamic structures for articulating and sequencing of behavior primitives are self-organized in the hierarchically organized network; and 3) such structures can afford both generalization and context dependency in generating skilled behaviors. 相似文献
995.
996.
This paper proposes a probabilistic variant of the SOM-kMER (Self Organising Map-kernel-based Maximum Entropy learning Rule)
model for data classification. The classifier, known as pSOM-kMER (probabilistic SOM-kMER), is able to operate in a probabilistic
environment and to implement the principles of statistical decision theory in undertaking classification problems. A distinctive
feature of pSOM-kMER is its ability in revealing the underlying structure of data. In addition, the Receptive Field (RF) regions
generated can be used for variable kernel and non-parametric density estimation. Empirical evaluation using benchmark datasets
shows that pSOM-kMER is able to achieve good performance as compared with those from a number of machine learning systems.
The applicability of the proposed model as a useful data classifier is also demonstrated with a real-world medical data classification
problem. 相似文献
997.
Batch Nearest Neighbor Search for Video Retrieval 总被引:2,自引:0,他引:2
Jie Shao Zi Huang Heng Tao Shen Xiaofang Zhou Ee-Peng Lim Yijun Li 《Multimedia, IEEE Transactions on》2008,10(3):409-420
To retrieve similar videos to a query clip from a large database, each video is often represented by a sequence of high- dimensional feature vectors. Typically, given a query video containing m feature vectors, an independent nearest neighbor (NN) search for each feature vector is often first performed. After completing all the NN searches, an overall similarity is then computed, i.e., a single content-based video retrieval usually involves m individual NN searches. Since normally nearby feature vectors in a video are similar, a large number of expensive random disk accesses are expected to repeatedly occur, which crucially affects the overall query performance. Batch nearest neighbor (BNN) search is stated as a batch operation that performs a number of individual NN searches. This paper presents a novel approach towards efficient high-dimensional BNN search called dynamic query ordering (DQO) for advanced optimizations of both I/O and CPU costs. Observing the overlapped candidates (or search space) of a pervious query may help to further reduce the candidate sets of subsequent queries, DQO aims at progressively finding a query order such that the common candidates among queries are fully utilized to maximally reduce the total number of candidates. Modelling the candidate set relationship of queries by a candidate overlapping graph (COG), DQO iteratively selects the next query to be executed based on its estimated pruning power to the rest of queries with the dynamically updated COG. Extensive experiments are conducted on real video datasets and show the significance of our BNN query processing strategy. 相似文献
998.
HU Jun GUAN Chun CHEN Yu-hai 《通讯和计算机》2008,5(5):16-20
To improve the ability of agent for handling emotions, a new architecture for emotion agent is presented, based on the traditional BDI agent model and the rough set theory. By a new emotional reasoning algorithm based on rough set, the architecture performs emotion reasoning and implements the emotion treatment. An emotional agent grid based on this architecture has been realized, experiment results show that it is efficient to transact simple emotions by emotional agents. 相似文献
999.
Leveraging online communities in fostering adaptive schools 总被引:1,自引:0,他引:1
David Hung Kenneth Y. T. Lim Der-Thanq Victor Chen Thiam Seng Koh 《International Journal of Computer-Supported Collaborative Learning》2008,3(4):373-386
There has long been a call for schools to prepare students for the twenty-first century where skills and dispositions differ
significantly from much of what has historically characterized formal education. The knowledge based economy calls for policy
and pedagogical efforts that would transform schools. Schools are to foster communities of learners. This paper suggests that
para-communities may be points of leverage in the fostering of adaptive schools. A critical analysis is done on the differences
between para-communities (such as online communities) and schools; and an argument is made that they each serve differing
goals and should be left distinct because they achieve different societal and economic demands. 相似文献
1000.
The filtering problem for continuous‐time linear systems with unknown parameters is considered. A new suboptimal filter is herein proposed. It is based on the optimal mean‐square linear combination of the local Kalman filters. In contrast to the optimal weights, the suboptimal weights do not depend on current observations; thus, the proposed filter can easily be implemented in real‐time. Examples demonstrate high accuracy and efficiency of the suboptimal filter. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society 相似文献