To solve the high complexity of the subspace-based direction-of-arrival (DOA) estimation algorithm, a super-resolution DOA algorithm is built in this paper. However, in this method, matrix decomposition is required fo...
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To solve the high complexity of the subspace-based direction-of-arrival (DOA) estimation algorithm, a super-resolution DOA algorithm is built in this paper. However, in this method, matrix decomposition is required for each search angle. Therefore, in this paper, real-valued processing is used to reduce the scanning range by half, which is less effective in algorithm complexity. The super-resolution algorithm mainly uses the conservation of energy. By exploring the relationship between the covariance matrix and its complex conjugate, we constructed the real-valued matrix and introduced a real-valued searching source to make the operation of the matrix real-valued. Finally, the simulation experiments show that the proposed algorithm not only reduces the spectral search range by half but also has a higher angular resolution than the traditional algorithm.
In this paper a new efficient algorithm is proposed for testing the truth of assertions for real numbers expressed in relational signatures. In contrast to the well known Tarski algorithm, the proposed algorithm reduc...
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In this paper a new efficient algorithm is proposed for testing the truth of assertions for real numbers expressed in relational signatures. In contrast to the well known Tarski algorithm, the proposed algorithm reduces the search problem of checking the truth of any assertion for real numbers to the optimization problem. The new version of the algorithm can be used for algebraic and transcendental functions.
The general problem of tiling finite regions of the plane with polyominoes is NP-complete, and so the associated computational geometry problem rapidly becomes intractable for large instances. Thus, the need to reduce...
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The general problem of tiling finite regions of the plane with polyominoes is NP-complete, and so the associated computational geometry problem rapidly becomes intractable for large instances. Thus, the need to reduce algorithm complexity for tiling is important and continues as a fruitful area of research. Traditional approaches to tiling with polyominoes use backtracking, which is a refinement of the 'brute-force' solution procedure for exhaustively finding all solutions to a combinatorial search problem. In this work, we combine checkerboard colouring techniques with a recently introduced integer linear programming (ILP) technique for tiling with polyominoes. The colouring arguments often split large tiling problems into smaller subproblems, each represented as a separate ILP problem. Problems that are amenable to this approach are embarrassingly parallel, and our work provides proof of concept of a parallelizable algorithm. The main goal is to analyze when this approach yields a potential parallel speedup. The novel colouring technique shows excellent promise in yielding a parallel speedup for finding large tiling solutions with ILP, particularly when we seek a single (optimal) solution. We also classify the tiling problems that result from applying our colouring technique according to different criteria and compute representative examples using a combination of MATLAB and CPLEX, a commercial optimization package that can solve ILP problems. The collections of MATLAB programs PARIOMINOES (v3.0.0) and POLYOMINOES (v2.1.4) used to construct the ILP problems are freely available for download.
The problem of determining whether it is possible for a set of “free-running” processes to become deadlocked is considered. It is assumed that any request by a process is immediately granted as long as there are eno...
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The problem of determining whether it is possible for a set of “free-running” processes to become deadlocked is considered. It is assumed that any request by a process is immediately granted as long as there are enough free resource units to satisfy the request. The question of whether or not there exists a polynomial algorithm for predicting deadlock in a “claim-limited” serially reusable resource system has been open. An algorithm employing a network flow technique is presented for this purpose. Its running time is bounded by O(mn1.5) if the system consists of n processes sharing m types of serially reusable resources.
Over the last decade, smart sensors have grown in complexity and can now handle multiple measurement sources. This work establishes a methodology to achieve better estimates of physical values by processing raw measur...
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Over the last decade, smart sensors have grown in complexity and can now handle multiple measurement sources. This work establishes a methodology to achieve better estimates of physical values by processing raw measurements within a sensor using multi-physical models and Kalman filters for data fusion. A driving constraint being production cost and power consumption, this methodology focuses on algorithmic complexity while meeting real-time constraints and improving both precision and reliability despite low power processors limitations. Consequently, processing time available for other tasks is maximized. The known problem of estimating a 2D orientation using an inertial measurement unit with automatic gyroscope bias compensation will be used to illustrate the proposed methodology applied to a low power STM32L053 microcontroller. This application shows promising results with a processing time of 1.18 ms at 32 MHz with a 3.8% CPU usage due to the computation at a 26 Hz measurement and estimation rate.
We show that n-way plurality voting on a large unordered object space has time and space complexities of θ(n 2 ) and θ(n), respectively. If the object space is ordered, then sorting can be used to reduce the time co...
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We show that n-way plurality voting on a large unordered object space has time and space complexities of θ(n 2 ) and θ(n), respectively. If the object space is ordered, then sorting can be used to reduce the time complexity to the optimal θ(n log n). We then prove that weighted t- out-of -∑v i threshold voting on such an object space has time complexity O(np) and needs working storage space for only p objects, where p=[(∑v i )/t]. Thus, unless t is very small, threshold voting is considerably simpler than plurality voting. As a corollary, weighted majority voting can be performed in linear time with working storage for a single input object.
The wireless transmission characteristics of RFID system is vulnerable to be attacked and theft within communication,to people adopt the physical methods and authentication encryption methods to enhance system securit...
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The wireless transmission characteristics of RFID system is vulnerable to be attacked and theft within communication,to people adopt the physical methods and authentication encryption methods to enhance system security,authentication encryption methods is more useful due to its simple *** this paper,we analysis of security vulnerabilities exist in the commonly used authentication protocol based on Hash function,on this basis bring forward a modified *** compare them in security,data storage condition and complexity of the algorithm,it can prove that the improved protocol has a very good improvement for RFID system’s overall performance,particularly in security.
Based on the classic dynamic programming solution to solve the 0-1 knapsack problem,we give an improved algorithm called ***,in order to decrease the space complexity of IKP,we combine divided-and-conquered strategy w...
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Based on the classic dynamic programming solution to solve the 0-1 knapsack problem,we give an improved algorithm called ***,in order to decrease the space complexity of IKP,we combine divided-and-conquered strategy with IKP to obtain a new algorithm *** Analysis shows that DKP has a great advantage over IKP in running time and resource ***,DKP has a better time complexity than some known algorithms for the 0-1 knapsack problem,and it has high parallel,in which way DKP can relief the tension of memory cost.
The paper describes the basic concepts of rough set theory and discernibility matrix and presents an attribute reduction algorithm based on reduced discernibility matrix,which aims at resolving the inadequate of the e...
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The paper describes the basic concepts of rough set theory and discernibility matrix and presents an attribute reduction algorithm based on reduced discernibility matrix,which aims at resolving the inadequate of the existing attribute reduction based on incomplete decision *** only contain useful elements for the algorithm in the reduced discernibility matrix,which obtain one reduction of incomplete decision table by iteration and set *** experimental results show that the algorithm can not only obtain reduced attribute,but also reduce the computation time and storage space greatly.
In this paper,Structure and properties of neural networks with quadratic junction are *** learning rules about the neural networks are *** this kind of neural networks,an ART-based hierarchical clustering algorithm is...
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In this paper,Structure and properties of neural networks with quadratic junction are *** learning rules about the neural networks are *** this kind of neural networks,an ART-based hierarchical clustering algorithm is *** algorithm can determine the number of clusters and clustering *** time and space complexity of the algorithm are discussed.A 2-D artificial data set is used to illustrate and compare the effectiveness of the proposed algorithm and K-means algorithm.
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