Elastic Characteristic Extraction Method of Underwater Target Based on Adaptive Filtering

In this paper, a kind of elastic characteristic extraction method of underwater targets based on adaptive filtering is introduced. The kernel of the method is the recursive least square （RLS） algorithm. Firstly, the geometric scattering signal is fit by using the echo signal and the incident signal. Then, the frequency spectrum of the echo signal and the geometric scattering signal are calculated. At last, the frequency spectrum of the elastic scattering signal is obtained. The research of the simulation and lake experiment is carried on. As the results show, the formants of the elastic signal frequency spectrum can be precisely extracted by the algorithm, and the extraction algorithm can apply to extracting the elastic characteristic from the echo signal in a real underwater acoustics environment.

PARALLEL ADAPTIVELY MODIFIED CHARACTERISTIC BASIS FUNCTION METHOD BASED ON STATIC LOAD BALANCE

Characteristic Basis Function Method (CBFM) is a novel approach for analyzing the ElectroMagnetic (EM) scattering from electrically large objects. Based on dividing the studied object into small blocks, the CBFM is suitable for parallel computing. In this paper, a static load balance parallel method is presented by combining Message Passing Interface (MPI) with Adaptively Modified CBFM (AMCBFM). In this method, the object geometry is partitioned into distinct blocks, and the serial number of blocks is sent to related nodes according to a certain rule. Every node only needs to calculate the information on local blocks. The obtained results confirm the accuracy and efficiency of the proposed method in speeding up solving large electrical scale problems.

Telemetric Data Reveals Ecolgoically Adaptive Behavior of Captive Raised Chinese Giant Salamanders When Reintroduced into Their Native Habitat

Little is known about the ecology of the Chinese Giant Salamander(Andrias davidianus), a critically endangered species. Such information is needed to make informed decisions concerning the conservation and management of this species. Four A. davidianus raised in a pool were released into their native habitat on 04 May 2005 and were subsequently radio-tracked for approximately 155–168 days. Following their release, the giant salamanders traveled upstream in search of suitable micro-habitats, and settled after 10 days. Later, a devastating summer flash flood destroyed the salamanders' dens, triggering another bout of habitat searching by the animals. Eventually, the salamanders settled in different sections of the stream where they remained until the end of the study. On average, each habitat searching endeavor took 7.5 days, during which a giant salamander explored a 310 m stretch of stream with a surface area of about 1157 m2 and occupied 3.5 temporary dwellings. Each giant salamander spent an average of 144.5 days in semi-permanent micro-habitats, and occupied territories that had a mean size of 34.75 m2. Our results indicate that the Chinese giant salamander responds to habitat disturbance by seeking new habitats upstream, both water temperature and water level affect the salamander's habitat searching activity, and the size of the salamander's semi-permanent territory is influenced by the size of the pool containing the animal's den.

Characteristic model-based consensus of networked heterogeneous robotic manipulators with dynamic uncertainties

In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.