Improved Relaxation Algorithm Research Articles

Research on frequency shift signal detection algorithm for jointless track circuits based on improved relaxation algorithm

The accuracy of ZPW-2000 frequency shift signal demodulation is related to the safety and efficiency of high-speed trains. This paper proposed a kind of ZPW-2000 frequency-shift signal detection algorithm based on improved Relaxation algorithm (ZFSD-IR) to address the issue of low accuracy in detecting ZPW-2000 frequency shift signal under strong noise interference, as the traditional fast Fourier transform (FFT) spectrum analysis methods are susceptible to fence effects and spectrum leakage effects. Firstly, the principle of ZPW-2000 jointless track circuit was analyzed, and then the ideal and simplified models of ZPW-2000 frequency shift signal were established, respectively. Finally, the simulation experiments were conducted on ZPW-2000 frequency shift signal detection under different sampling durations and signal-to-noise ratios (SNR). The effectiveness of the proposed algorithm was verified through comparative analysis with the traditional algorithms. The research results indicated that the ZFSD-IR algorithm has better accuracy in carrier-frequency and low-frequency estimation than traditional algorithms, and can achieve accurate detection of ZPW-2000 frequency shift signal under the lower SNR conditions. It has high detection accuracy and good anti-interference ability, ensuring the safe operation of high-speed trains.

A real-time pricing mechanism considering data freshness based on non-cooperative game in crowdsensing

A fair and reasonable price mechanism is fundamental in improving the efficiency of the crowdsensing market. Being an emerging paradigm that utilizes widely distributed wireless communication network and smart sensing devices to collect sensing data, crowdsensing service offers a plausibility for collecting real-time data. However, previous studies ignored the complex competition among participants in the free data trade market and the fresh data demands of increasingly popular real-time applications. This paper introduces the age of information (AoI) as a criterion to measure the freshness of data geared towards constructing incentive models for the data provider and data requester. Subsequently, considering the opening of the market, we design a price mechanism framework based on non-cooperative games, which can help the crowdsensing platform provide each participant a stable sensing strategy to maximize profit. For the AoI-sensitive case, i.e., when the data quality deteriorates with the time. A co-evolutionary algorithm based on heuristic search is designed to solve the sensing strategy for each provider to achieve Nash equilibrium. Furthermore, for the case where AoI is insensitive. An improved relaxation algorithm is proposed to provide a stable strategy for the data provider. Numerical findings reveal that the developed algorithm can effectively identify stable sensing strategies in a Nash equilibrium.

Attributed Scattering Center Extraction With Genetic Algorithm

An attributed scattering center (ASC) model provides concise and physically relevant features for complex targets and plays an important role in inverse scattering problems. Extracting ASC features from a radar image is designed to solve a highly nonlinear and nonconvex optimization problem, which requires an accurate yet complex parameter initialization process and generates intensive computation and storage cost. This article presents an ASC feature extraction method with a genetic algorithm (GA) (AFEM-GA). The proposed AFEM-GA utilizes an improved real-coded GA to search for the global optimum for each ASC feature in the radar frequency-aspect angle domain in parallel, without complex parameter initialization and with low computation and storage costs. Moreover, an improved relaxation algorithm is also proposed for multiple ASC feature extractions to avoid error accumulation. Experiments based on both numerical computed data and real data verify the accuracy and robustness of the proposed AFEM-GA and show its potential in radar image interpretation.

Improved relaxation algorithm for passive sensor data association

The Lagrangian relaxation algorithm is widely used for passive sensor data association. However, there are two major problems about it. Firstly, the cost function of the algorithm is computed by using least square estimation of the target position without taking the estimation errors into account. To solve this problem, a modified cost function is derived which can reflect the correlation between measurements more reasonably owing to the integration of estimation errors. Secondly, due to the fact that building the candidate assignment tree would take a lot of CPU time, we propose a statistic test based on indicator function with a great improvement of the computational efficiency. Simulation results show that both the correlation accuracy and the computational efficiency of the improved relaxation algorithm are higher than that of the traditional one.

Shape influences on the packing density of frustums

The shape of a frustum is a bivariate function of aspect ratio (w) and base radii ratio (c). To investigate the shape influences on the packing density of frustums, random packings of cones (c=0), truncated cones and cylinders (c=1) with various heights and diameters are studied through numerical simulations. An improved relaxation algorithm with assembly sphere models for non-spherical particles is applied in the numerical simulations, and the randomness of the packings of the frustums considered is verified. Base on the simulation results, the relationship between the packing density and shape parameters is illustrated, and an empirical formula is proposed to reflect the correlation. It shows that, for the particles having the same w, truncated cones can be packed denser than cones, but looser than cylinders. The packing density of truncated cones first increases and then decreases with the growth of w, while the packing density increases monotonically with the increase of c. No obvious peak is found on the curve of packing density versus c for the random packing of truncated cones, which is different from the reported results for ordered packing where a peak was identified. Furthermore, we observe that the packing density of truncated cones is a linear superposition of the c effect on w effect, and the effects of c and w on the packing density can be treated independently. The optimal aspect ratios of truncated cones, which give the highest packing densities, are all around 0.8. The highest packing densities of cylinders and cones are also the upper and lower bound of the random packing density of truncated cones.

Modified cost function for passive sensor data association

The Lagrangian relaxation algorithm is an effective approach to solve the problem of passive sensor data association. However, the cost function of the algorithm is computed by using least squares estimation of the target position without taking the estimation errors into account. To solve this problem, a modified cost function is derived, which can reflect the correlation between measurements more reasonably owing to the integration of estimation errors. The simulation results show that the improved relaxation algorithm based on the modified cost function has better performance than the original one, implying good application prospects.

Full dimensional (15 dimensional) quantum-dynamical simulation of the protonated water-dimer IV: Isotope effects in the infrared spectra of D(D2O)2+, H(D2O)2+, and D(H2O)2+ isotopologues

The infrared spectra of H(H(2)O)(2)(+), D(D(2)O)(2)(+), H(D(2)O)(2)(+), and D(H(2)O)(2)(+) isotopologues of the Zundel cation in the spectral range of 0-4000 cm(-1) are computed by quantum dynamics in full dimensionality using the multiconfiguration time-dependent Hartree method. The spectra present dramatic isotope effects in the middle spectral region between 600 and 2000 cm(-1). Not only the expected line shifts due to isotopic substitution take place but the intensities of the peaks and the number of absorptions with appreciable intensity vary. The most complex spectrum is the one of H(D(2)O)(2)(+), in which a group of at least four coupled vibrational modes is found in a narrow spectral range between 1000 and 1500 cm(-1) and is responsible for the three peaks found in this spectral region. The simplest spectrum of the series corresponds to D(H(2)O)(2)(+). In this case deuteration of the central position induces decoupling of the vibrational modes, especially of the asymmetric central proton mode and the ungerade water bending, leading to a spectrum which is easy to assign and interpret. Zero-point energies and low energy vibrational eigenstates of each isotopologue related to the wagging (pyramidalization) and water-water internal relative rotation are computed using the block improved relaxation algorithm. The effect of isotopic substitution on these states is discussed. The reported simulations provide detailed information on the dynamics and vibrational spectroscopy of the Zundel cation and contribute to our general understanding of protonated water clusters and the hydrated proton.

Numerical Simulation of Random Close Packings in Particle Deformation from Spheres to Cubes

Variation of packing density in particle deforming from spheres to cubes is studied. A new model is presented to describe particle deformation between different particle shapes. Deformation is simulated by relative motion of component spheres in the sphere assembly model of a particle. Random close packings of particles in deformation form spheres to cubes are simulated with an improved relaxation algorithm. Packings in both 2D and 3D cases are simulated. With the simulations, we find that the packing density increases while the particle sphericity decreases in the deformation. Spheres and cubes give the minimum (0.6404) and maximum (0.7755) of packing density in the deformation respectively. In each deforming step, packings starting from a random configuration and from the final packing of last deforming step are both simulated. The packing density in the latter case is larger than the former in two dimensions, but is smaller in three dimensions. The deformation model can be applied to other particle shapes as well.

Numerical Simulation of Random Close Packing with Tetrahedra

The densest packing of tetrahedra is still an unsolved problem. Numerical simulations of random close packing of tetrahedra are carried out with a sphere assembly model and improved relaxation algorithm. The packing density and average contact number obtained for random close packing of regular tetrahedra is 0.6817 and 7.21 respectively, while the values of spheres are 0.6435 and 5.95. The simulation demonstrates that tetrahedra can be randomly packed denser than spheres. Random close packings of tetrahedra with a range of height are simulated as well. We find that the regular tetrahedron might be the optimal shape which gives the highest packing density of tetrahedra.

Polarization imaging for 3D inspection of highly reflective metallic objects

In the field of industrial vision, the 3D inspection of highly reflective metallic objects is still a delicate task. The specular reflections prevent the use of a 3D laser scanner, whereas the phase shifting-based 3D systems are more adapted to inspect surfaces with low curvature. This paper deals with a new automated 3D inspection system based on polarization analysis. Studying the state of polarization of the reflected light is very useful for obtaining information on the normals of the surface. An extension of the shape from polarization method from dielectric to metallic surfaces is demonstrated. Then, an improved relaxation algorithm is provided in order to reconstruct the shape from the normal field given by the polarization analysis. Finally, applications to shape defect detection are discussed and the efficiency of the system in discriminating defects on highly reflective metallic objects made by stamping and polishing is presented.