Inversion of Seabed Geotechnical Properties in the Arctic Chukchi Deep Sea Basin Based on Time Domain Adaptive Search Matching Algorithm

The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained based on the chirp sub-bottom profiler data collected in the Chukchi Plateau area during the 11th Arctic Expedition of China.The time-domain adaptive search matching algorithm was used and validated on our established theoretical model.The misfit between the inversion result and the theoretical model is less than 0.067%.The grain size was calculated according to the empirical relationship between the acoustic impedance and the grain size of the sediment.The average acoustic impedance of sub-seafloor strata is 2.5026×10^(6) kg(s m^(2))^(-1)and the average grain size(θvalue)of the seafloor surface sediment is 7.1498,indicating the predominant occurrence of very fine silt sediment in the study area.Comparison of the inversion results and the laboratory measurements of nearby borehole samples shows that they are in general agreement.

Improving the reconstruction efficiency of sparsity adaptive matching pursuit based on the Wilkinson matrix

Sparsity adaptive matching pursuit(SAMP)is a greedy reconstruction algorithm for compressive sensing signals.SAMP reconstructs signals without prior information of sparsity and presents better reconstruction performance for noisy signals compared to other greedy algorithms.However,SAMP still suffers from relatively poor reconstruction quality especially at high compression ratios.In the proposed research,the Wilkinson matrix is used as a sensing matrix to improve the reconstruction quality and to increase the compression ratio of the SAMP technique.Furthermore,the idea of block compressive sensing(BCS)is combined with the SAMP technique to improve the performance of the SAMP technique.Numerous simulations have been conducted to evaluate the proposed BCS-SAMP technique and to compare its results with those of several compressed sensing techniques.Simulation results show that the proposed BCS-SAMP technique improves the reconstruction quality by up to six decibels(d B)relative to the conventional SAMP technique.In addition,the reconstruction quality of the proposed BCS-SAMP is highly comparable to that of iterative techniques.Moreover,the computation time of the proposed BCS-SAMP is less than that of the iterative techniques,especially at lower measurement fractions.

Adaptive detection in the presence of signal mismatch

The problem of adaptive detection in the situation of signal mismatch is considered; that is, the actual signal steering vector is not aligned with the nominal one. Two novel tunable detectors are proposed. They can control the degree to which the mismatched signals are rejected. Remarkably, it is found that they both cover existing famous detectors as their special cases. More importantly, they possess the constant false alarm rate（CFAR）property and achieve enhanced mismatched signal rejection or improved robustness than their natural competitors. Besides, they can provide slightly better matched signals detection performance than the existing detectors.

Experimental research on adaptive match of ocean sound channel

In this paper based on the study of time-space-variant characteristics of ocean sound Channel, the channel response function is found by adaptive filtering. The obtained channel′s response function is applied to match the channel and satisfactory effect is shown. In the case of time-invariant channel the key problem is how to increase the convergent speed of adaptive match algorithm. For this purpose, besides using an adaptive step size factor and performing adaptive filtering in the filtering in the frequency domain, a rational selection of the weight parameters (the number of weights and the time relationship between the weights) is proposed.The result shows that under the condition of rational selection of the weight parameters a complicated response function of the channel can be expressed by a limited number of weights.

Response of adaptive matched filter to multipath channel

Response of adaptive matched filter, also called adaptive correlator, to multipath channel is discussed in this paper. It has been proved that the new type processor can better match with multipath chan -nel. The results of experiment carried out on lake and in laboratory are presented. It shows that the processor has good detecting performance in time domain.

A New Two-Stage Tunable Space-Time Adaptive Detector

In order to improve the rejection capability of mismatched interferer signals,a new two-stage detector is proposed under homogeneous scenarios with unknown covariance matrix,which is obtained by cascading the adaptive matched filter(AMF)detector and the enhanced RAO(EnRAO)detector.The new detector has constant false alarm performance,and the closed-form expression of probability of false alarm and probability of detection is derived.The performance of the new detector is assessed,and analyzed in comparison with other detectors.The results show that,the proposed detector can provide enhanced rejection capability in the case of mismatch,but the performance of the detector is slightly lost under the condition of matching.

Hilbert-Huang transform with adaptive waveform matching extension and its application in power quality disturbance detection for microgrid

With the significant improvement of microgrid technology, microgrid has gained large-scale application.However, the existence of intermittent distributed generations, nonlinear loads and various electrical and electronic devices causes power quality problem in microgrid, especially in islanding mode. An accurate and fast disturbance detection method which is the premise of power quality control is necessary. Aiming at the end effect and the mode mixing of original Hilbert-Huang transform(HHT), an improved HHT with adaptive waveform matching extension is proposed in this paper. The innovative waveform matching extension method considers not only the depth of waveform, but also the rise time and fall time. Both simulations and field experiments have verified the correctness and validity of the improved HHT for power quality disturbance detection in microgrid.

Agroforestry Suggestions Based on Climatic Modeling

Indigenous agroforestry systems have been practiced for centuries in the Himalaya Mountains and adjoining regions.With the increase of climate change associated risks,enhanced understanding of the impact of climate change and related phenomena on the potential distribution of agroforestry is increasingly useful and necessary,for both maintaining and improving yield and ecosystem function.In particular,

A Modified Multiple Matching Method Based on Equipoise Pseudomulti-Channel Filter and Huber Nor

This study is aimed at improving multiple adaptive subtraction.We propose a modified pseudomulti-channel matching method based on the Huber norm,to adjust the matching differences on frequency and phase between the predicted multi-ples and original data.The second-order derivative of the predicted multiples is utilized to replace the derivative of its Hilbert transform.Due to the additional frequency term,this method can enhance the high-frequency component.We introduce 180◦phase rotation of the multiple channels,which can decrease phase differences.The Huber norm interpolates between smooth L2 norm treatment of small residuals and robust L1 norm treatment of large residuals.This method can eliminate the restriction of large value conditions from the L2 norm and weaken the condition of orthogonality from the L1 norm.The applications of the Pluto and Delft models shows that compared with pseudomulti-channel matching filter,the main frequency is increased from 36 Hz to 38 Hz,and the primary reflection wave is more concentrated.The practical application of field data verifies the effectiveness of the proposed method.

Design and Tool Flow of a Reconfigurable Asynchronous Neural Network Accelerator

Convolutional Neural Networks(CNNs)are widely used in computer vision,natural language processing,and so on,which generally require low power and high efficiency in real applications.Thus,energy efficiency has become a critical indicator of CNN accelerators.Considering that asynchronous circuits have the advantages of low power consumption,high speed,and no clock distribution problems,we design and implement an energy-efficient asynchronous CNN accelerator with a 65 nm Complementary Metal Oxide Semiconductor(CMOS)process.Given the absence of a commercial design tool flow for asynchronous circuits,we develop a novel design flow to implement Click-based asynchronous bundled data circuits efficiently to mask layout with conventional Electronic Design Automation(EDA)tools.We also introduce an adaptive delay matching method and perform accurate static timing analysis for the circuits to ensure correct timing.The accelerator for handwriting recognition network(LeNet-5 model)is implemented.Silicon test results show that the asynchronous accelerator has 30%less power in computing array than the synchronous one and that the energy efficiency of the asynchronous accelerator achieves 1.538 TOPS/W,which is 12%higher than that of the synchronous chip.