A comparative study of nonlinear filtering techniques

Abstract-In a recent work it is shown that importance sampling can be avoided in the particle filter through an innovation structure inspired by traditional nonlinear filtering combined with optimal control formalisms. The resulting algorithm is referred to as feedback particle filter. The purpose of this paper is to provide a comparative study of the feedback particle filter (FPF). Two types of comparisons are discussed: i) with the extended Kalman filter, and ii) with the conventional resampling-based particle filters. The comparison with Kalman filter is used to highlight the feedback structure of the FPF. Also computational cost estimates are discussed, in terms of number of operations relative to EKF. Comparison with the conventional particle filtering approaches is based on a numerical example taken from the survey article on the topic of nonlinear filtering A secondary purpose of this paper is to provide a summary of the FPF algorithm, that can aid practitioners to rapidly implement the algorithm. A detailed algorithm (pseudo-code) is included, and compared against an EKF algorithm. Such comparisons also help highlight the feedback structure of the FPF algorithm

Comparative Assessment of Feed-forward Schemes with NCTF for Sway and Trajectory Control of a DPTOC

This paper presents a comparative assessment of feed-forward schemes in hybrid control schemes for anti-swaying and trajectory tracking of a double-pendulum-type overhead crane (DPTOC) system. A nonlinear DPTOC system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. To study the effectiveness of the controllers, initially nominal characteristics following trajectory following (NCTF) is developed for position control of cart movement. The controller design, which is comprised of a nominal characteristic trajectory (NCT) and PI compensator, is used to make the cart motion follow the NCT. This is then extended to incorporate feed-forward schemes for anti-swaying control of the system. Feed-forward control schemes based on input shaper and filtering techniques are to be examined. The input shaper and filtering techniques with different orders were designed based on properties of the system. The results of the response with the controllers are presented in time and frequency domains. The performances of hybrid control schemes are examined in terms of level of input tracking capability, sway angle reduction and time response specifications in comparison to NCTF controller. Finally, a comparative assessment of the control techniques is discussed and presented

Distinguishing niche and neutral processes: issues in variation partitioning statistical methods and further perspectives

Variance partitioning methods, which are built upon multivariate statistics, have been widely applied in different taxa and habitats in community ecology. Here, I performed a literature review on the development and application of the methods, and then discussed the limitation of available methods and the difficulties involved in sampling schemes. The central goal of the work is then to propose some potential practical methods that might help to overcome different issues of traditional least-square-based regression modeling. A variety of regression models has been considered for comparison. In initial simulations, I identified that generalized additive model (GAM) has the highest accuracy to predict variation components. Therefore, I argued that other advanced regression techniques, including the GAM and related models, could be utilized in variation partitioning for better quantifying the aggregation scenarios of species distribution.Comment: 19 pages; 4 figure

Effective denoising and adaptive equalization of indoor optical wireless channel with artificial light using the discrete wavelet transform and artificial neural network

Indoor diffuse optical wireless (OW) communication systems performance is limited due to a number of effects; interference from natural and artificial light sources and multipath induced intersymbol interference (ISI). Artificial light interference (ALI) is a periodic signal with a spectrum profile extending up to the MHz range. It is the dominant source of performance degradation at low data rates, which can be removed using a high-pass filter (HPF). On the other hand, ISI is more severe at high data rates and an equalizing filter is incorporated at the receiver to compensate for the ISI. This paper provides the simulation results for a discrete wavelet transform (DWT)—artificial neural network (ANN)-based receiver architecture for on-and-off keying (OOK) non-return-to-zero (NRZ) scheme for a diffuse indoor OW link in the presence of ALI and ISI. ANN is adopted for classification acting as an efficient equalizer compared to the traditional equalizers. The ALI is effectively reduced by proper selection of the DWT coefficients resulting in improved receiver performance compared to the digital HPF. The simulated bit error rate (BER) performance of proposed DWT-ANN receiver structure for a diffuse indoor OW link operating at a data range of 10-200 Mbps is presented and discussed. The results are compared with performance of a diffuse link with an HPF-equalizer, ALI with/without filtering, and a line-of-sight (LOS) without filtering. We show that the DWT-ANN display a lower power requirement when compared to the receiver with an HPF-equalizer over a full range of delay spread in presence of ALI. However, as expected compared to the ideal LOS link the power penalty is higher reaching to 6 dB at 200 Mbps data rate