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In the present article, we extend the results of the neural network interpolation operators activated by smooth ramp functions proposed by Yu (Acta Math. Sin.(Chin. Ed.) 59:623-638, 2016). We give different results from Yu (Acta Math. Sin.(Chin. Ed.) 59:623-638, 2016) we discuss the high-order approximation result using the smoothness of φ and a related Voronovskaya-type asymptotic expansion for the error of approximation. In addition, we showcase the related fractional estimates result and the fractional Voronovskaya type asymptotic expansion. We investigate the approximation degree for the iterated and complex extensions of the aforementioned operators. Finally, we provide numerical examples and graphs to effectively illustrate and validate our results. [ABSTRACT FROM AUTHOR]

This paper proposes a Generalized Multilevel B-spline Approximation (GMBA) method, which addresses scattered data interpolation problems in image processing. Mathematically, the GMBA provides a better solution for the B-spline control lattice by superimposing identical level B-splines compared with traditional Multilevel B-spline Approximation (MBA). Specifically, the GMBA allows the spacing of next control lattice to be subdivided arbitrarily or remained unchanged, which is determined by a predefined spacing set or the current error level. These improvements bring higher approximation accuracy and more flexibility for algorithm design to avoid over-fitting. In this paper, basic GMBA algorithm and its refined algorithm are compiled for image processing. Finally, six relevant cases are involved to test the GMBA, including surface approximation, image enlargement, image completion, and Salt-and-Pepper (SAP) noise removal. The experimental results show that the GMBA has better performance than the MBA in surface approximation and image processing, performs comparatively fast with the best performance on more than half of the standard test images compared with traditional algorithms, and has partially better performance even than deep learning algorithms. The GMBA can effectively recover meaningful details in images contaminated with even extremely high SAP noise level (up to 99%). • We give a generalized multilevel B-spline approximation (GMBA) method. • GMBA allows the control spacing to be subdivided arbitrarily or remained unchanged. • GMBA offers higher approximation accuracy and greater flexibility than traditional MBA. • GMBA provides superior performance and less run time than many of the state-of-the-art methods for SAP noise removal. • GMBA can recovery meaningful detail at noise levels as high as 99% for SAP noise removal. [ABSTRACT FROM AUTHOR]

Let ω be a positive, Lebesgue integrable and exponential decay function defined on an infinite interval I and let L1,ω(I) be the space of weighted Lebesgue integrable functions on I. In this paper, we give the relations of the best one-sided approximation and the optimal Hermite–Fejér interpolation by the set of algebraic polynomials of degree not exceeding a given number for the smooth function classes BC2r,+(I), r ∈ ℕ+, in the metric of the space L1,ω(I), and prove that the Hermite–Fejér interpolation based on the set of the zeros of some orthogonal polynomials is optimal in L1,ω(I). In addition, we show that the approximation error of the optimal Hermite–Fejér interpolation and quadrature errors of the weighted Gaussian quadrature formula are equal, and give the exact constant of the errors. [ABSTRACT FROM AUTHOR]

The new iterative method of approximating the boundary trajectory of a short-focus electron beam propagating in a free drift mode in a low-pressure ionized gas under the condition of compensation of the space charge of electrons is considered and discussed in the article. To solve the given approximation task, the root-polynomial functions of the fourth and fifth order were applied, the main features of which are the ravine character and the presence of one global minimum. As an initial approach to solving the approximation problem, the values of the polynomial coefficients are calculated by solving the interpolation problem. After this, the approximation task is solved iteratively. All necessary polynomial coefficients are calculated multiple times, taking into account the values of the function and its derivative at the reference points. The final values of polynomial coefficients of high-order root-polynomial functions are calculated using the dichotomy method. The article also provides examples of the applying fourth-order and fifth-order root-polynomial functions to approximate sets of numerical data that correspond to the description of ravine functions. The obtained theoretical results are interesting and important for the experts who study the physics of electron beams and design modern industrial electron beam technological equipment. [ABSTRACT FROM AUTHOR]

In this work we extend some ideas about greedy algorithms, which are well-established tools for, e.g., kernel bases, and exponential-polynomial splines whose main drawback consists in possible overfitting and consequent oscillations of the approximant. To partially overcome this issue, we develop some results on theoretically optimal interpolation points. Moreover, we introduce two algorithms which perform an adaptive selection of the spline interpolation points based on the minimization either of the sample residuals (f-greedy), or of an upper bound for the approximation error based on the spline Lebesgue function (λ -greedy). Both methods allow us to obtain an adaptive selection of the sampling points, i.e., the spline nodes. While the f-greedy selection is tailored to one specific target function, the λ -greedy algorithm enables us to define target-data-independent interpolation nodes. [ABSTRACT FROM AUTHOR]

Signed distance fields (SDFs) have emerged as an alternative shape representation for real-time collision detection and lighting effects. Computing these for complex models can be expensive, so one popular approach is to prepare an approximation via sampling and interpolation. Then, these may be rendered using sphere marching, which gets close to the surface quickly, but needs several iterations to converge to it. In this paper, we propose an alternative that computes the intersection of a given ray and the surface analytically at a narrow band. This may be combined with other enhancements like having variable error for the approximation depending on the distance to the surface and skipping regions that do not contain the surface to accelerate the outer band ray traversal while reducing the required memory. To achieve smoother representations with minimal computational cost, we propose a method for computing surface intersections and normals from separate interpolants. We evaluate all these to find the optimal combination improving the rendering performance and memory consumption of these SDF approximations. [Display omitted] • Enhancements for rendering SDF piecewise approximations. • Solving narrow band intersections using analytical methods. • Reducing SDF approximations for improving required memory and outer band ray traversal. [ABSTRACT FROM AUTHOR]

High-dimensional dynamical systems often require computationally intensive physics-based simulations, making full physical space data assimilation impractical. Latent data assimilation methods perform assimilation in reduced-order latent space for efficiency but struggle with complex, nonlinear state-observation mappings. Recent solutions like Generalized Latent Data Assimilation (GLA) and Latent Space Data Assimilation (LSDA) address heterogeneous latent spaces by incorporating surrogate mapping functions but introduce computational costs and uncertainties. Furthermore, current algorithms that integrate data assimilation and deep learning still face limitations when it comes to handling non-explicit mapping functions. To address these challenges, this paper introduces a novel deep-learning-based data assimilation scheme, named Multi-domain Encoder–Decoder Latent Data Assimilation (MEDLA), capable of handling diverse data sources by sharing a common latent space. The proposed approach significantly reduces the computational burden since the complex mapping functions are mimicked by the multi-domain encoder–decoder neural network. It also enhances assimilation accuracy by minimizing interpolation and approximation errors. Extensive numerical experiments from three different test cases assess MEDLA's performance in high dimensional dynamical systems, benchmarking it against state-of-the-art latent data assimilation methods. The numerical results consistently underscore MEDLA's superiority in managing multi-scale observational data and tackling intricate, non-explicit mapping functions. [ABSTRACT FROM AUTHOR]

In this article, two new techniques of approximation of the reliability of a two-terminal network are developed based on the constructive theory of functions and related methods. Two methods of generating an approximation cubic spline are used: Lagrange-type interpolation procedures and Bernstein approximation operator. A possibility of minimizing the total error of approximation, based on keeping some properties invariant, is described in case of a large class of pairs of dual two-terminal networks. Simulations are included, showing that the error of approximation is negligible in case of some special initial data. [ABSTRACT FROM AUTHOR]

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In contour machining, contour error is a major factor affecting machining quality. In order to improve the performance of contour following, many control techniques based on real-time contour error estimation have been developed. In this paper, a Double Circle contour error estimation method is proposed. First, based on the kinematic information of the reference point on the command trajectory, five interpolation points closest to the actual point are obtained. Then the approximate contour error is obtained by employing the Double Circle approximation method. Compared with the common contour error approximation methods, the proposed method can achieve high precision approximation. In addition, according to the proposed contour error approximation method, the cross-coupled control strategy is improved. Experiments prove the effectiveness of the proposed estimation method and control strategy. [ABSTRACT FROM AUTHOR]

The hierarchical deep-learning neural network (HiDeNN) is systematically developed through the construction of structured deep neural networks (DNNs) in a hierarchical manner, and a special case of HiDeNN for representing Finite Element Method (or HiDeNN-FEM in short) is established. In HiDeNN-FEM, weights and biases are functions of the nodal positions, hence the training process in HiDeNN-FEM includes the optimization of the nodal coordinates. This is the spirit of r-adaptivity, and it increases both the local and global accuracy of the interpolants. By fixing the number of hidden layers and increasing the number of neurons by training the DNNs, rh-adaptivity can be achieved, which leads to further improvement of the accuracy for the solutions. The generalization of rational functions is achieved by the development of three fundamental building blocks of constructing deep hierarchical neural networks. The three building blocks are linear functions, multiplication, and inversion. With these building blocks, the class of deep learning interpolation functions are demonstrated for interpolation theories such as Lagrange polynomials, NURBS, isogeometric, reproducing kernel particle method, and others. In HiDeNN-FEM, enrichment functions through the multiplication of neurons is equivalent to the enrichment in standard finite element methods, that is, generalized, extended, and partition of unity finite element methods. Numerical examples performed by HiDeNN-FEM exhibit reduced approximation error compared with the standard FEM. Finally, an outlook for the generalized HiDeNN to high-order continuity for multiple dimensions and topology optimizations are illustrated through the hierarchy of the proposed DNNs. [ABSTRACT FROM AUTHOR]

In this study, a polyhedral approximation method for reachable sets of linear delay systems is investigated. For a continuous linear system with multiple delays, the first Euler scheme combining with linear interpolation is used to transform it into a discrete one. Then a polyhedral approximation method based on optimisation techniques is proposed to compute the discrete reachable set. By specifying an approximation error and solving a finite number of convex optimisation problems, a polyhedron can be constructed as the approximation of the discrete reachable set. The approximation quality measured in Hausdorff distance can be directly controlled. Next, illustrated examples are given to demonstrate the effectiveness of the proposed method. Finally, the authors show some reachable sets of linear delay control systems, and they compare the proposed method with some other methods in the literature. Numerical results clearly show the superior performance of the proposed method. [ABSTRACT FROM AUTHOR]

This paper gives a kind of sharp simultaneous approximation error estimation of Birkhoff interpolation for all  1 ≤ p , q ≤ ∞ , 0 ≤ s ≤ r − 1 , ∥ (f − L r f) (s) ∥ p ≤ C (r , s , p , q) (b − a) r − s + 1 / p − 1 / q ∥ f (r) ∥ q , where f ∈ W q r [ a , b ] and L r is the Birkhoff interpolation based on r pairs of numbers (x i , k i) i = 1 r with its P o ́ lya interpolation matrix to be regular. First, based on the integral remainder formula of Birkhoff interpolation, we refer the computation of C (r , s , p , q) to the norm of an integral operator. Second, we refer the values of C (r , s , 1 , 1) and C (r , s , ∞ , ∞) to two explicit integral expressions and the value of C (r , s , 2 , 2) to the computation of the maximum eigenvalue of a Hilbert–Schmidt operator. At the same time, we give the corresponding sharp Wirtinger inequality (s = 0) and sharp Picone inequality (1 ≤ s ≤ r − 1). [ABSTRACT FROM AUTHOR]

Efficient hardware implementations routinely approximate mathematical functions with look-up tables, while keeping the error of the approximation under control. For a certain class of commonly occurring 1D functions, namely monotonically increasing or decreasing functions, we found that it is possible to approximate such functions by repeated application of a very low resolution 1D look-up table. There are many advantages to cascading multiple identical LUTs, including the promise of a very simple hardware design and the use of standard linear interpolation. Further, the complexity associated with unequal bin sizes can be avoided. We show that for realistic applications, including gamma correction, high dynamic range encoding and decoding curves, as well as tone mapping and inverse tone mapping applications, multiple cascaded look-up tables can reduce the approximation error by more than 50% compared to a single look-up table with the same total memory footprint. [ABSTRACT FROM AUTHOR]

Downsampling and the computation of the bandlimited interpolation of discrete-time signals are two important concepts in signal processing. In this paper we analyze the downsampling operation regarding its impact on the existence and computability of the bounded bandlimited interpolation. We assume that the discrete-time signal is obtained by downsampling the samples of a bounded bandlimited signal that vanishes at infinity, and we study two problems. First, we investigate the existence of the bounded bandlimited interpolation for such discrete-time signals from a signal theoretic perspective and show that there exist signals for which the bounded bandlimited interpolation does not exist. Second, we analyze the algorithmic generation of the bounded bandlimited interpolation, using the concept of Turing computability. Turing computability models what is theoretically implementable on a digital computer. Interestingly, it turns out that even if the bounded bandlimited interpolation exists analytically, it is not always computable, which implies that there exists no algorithm on a digital computer that can always compute it. Computability is important in order that the approximation error be controlled. If a signal is not computable, we cannot ascertain whether the computed signal is sufficiently close to the true signal, i.e., we cannot verify every approximation accuracy. [ABSTRACT FROM AUTHOR]

Time delay or the time-of-flight is a most frequently used parameter in many ultrasonic applications. Delay estimation is based on the sampled signal, so the resolution is limited by the sampling grid. Higher accuracy is available if the signal-to-noise ratio is high, then the subsample estimate is desired. Techniques used for subsample interpolation suffer from bias error. Time-of-flight estimation that is free from bias errors is required. The proposed subsample estimation works in the frequency domain; it is based on the cross-correlation peak temporal position. The phase of the cross-correlation frequency response becomes linear thanks to multiplication by the complex conjugate, and its inclination angle is proportional to the delay. Then, subsample interpolation becomes free from the bias error. Twelve algorithmic implementations of this technique have been proposed in this paper. All algorithmic implementations have been analyzed for bias and random errors using simulation and MATLAB codes are given as supplementary material. Comparison with best-performing interpolation techniques (spline approximation, cosine interpolation, carrier phase) is given for both bias and random errors. It was demonstrated that frequency domain interpolation has no bias errors, and noise performance is better or comparable to other subsample estimation techniques. Weighted regression using L2 norm minimization has the best performance: total errors (bias and random) are within 3% of theoretical lower bound. [ABSTRACT FROM AUTHOR]

Bird's eye view (BEV) generation from front‐looking video stream is considered an important pre‐processing task in various computer vision applications such as driver assistance systems. In this work, hardware implementation of this process using high‐level synthesis in Simulink environment has been considered for rapid prototyping under real‐time constraints. Traditionally, researchers have employed lookup table‐based approaches to circumvent the exorbitant cost of implementing arithmetic modules associated with the perspective transformation. The hardware implementation scheme proposed here, however, demonstrates that a polynomial approximation over the limited domain of the involved operands not only saves precious hardware resources but also provides better fixed‐point precision. Synthesis results on Zynq‐7000 FPGA show that the proposed circuit reduces the block memory utilisation by 9% compared to the lookup table‐based built‐in Simulink Vision HDL block. The proposed design evaluates the results in fixed‐point format which is essential for subsequent bilinear interpolation to produce high‐fidelity output frame, albeit at the cost of 4% increase in DSP48E utilisation. The approximation error of the proposed solution is less than quarter‐pixel on average. The proposed hardware has been integrated as an IP core in a hardware‐software co‐design system. The whole framework is publicly available to facilitate practitioners and researchers. [ABSTRACT FROM AUTHOR]

The modified improved interpolating moving least squares (MIIMLS) method for meshless approaches has been developed. In a meshless method, the approximation accuracy of the derivative is directly proportional to the simulation accuracy. For improving the approximation accuracy of a derivative, we propose MIIMLS using Chebyshev nodes. In the approximation of a function, the results of MIIMLS reach the precision limit. In the approximation of a derivative, the MIIMLS method has high approximation accuracy between the nodes as compared to the conventional methods. [ABSTRACT FROM AUTHOR]

Abstract Radial basis function-generated finite differences (RBF-FD) based on the combination of polyharmonic splines (PHS) with high degree polynomials have recently emerged as a powerful and robust numerical approach for the local interpolation and derivative approximation of functions over scattered node layouts. Among the key features, (i) high orders of accuracy can be achieved without the need of selecting a shape parameter or the issues related to numerical ill-conditioning, and (ii) the harmful edge effects associated to the use of high order polynomials (better known as Runge's phenomenon) can be overcome by simply increasing the stencil size for a fixed polynomial degree. The present study complements our previous results, providing an analytical insight into RBF-FD approximations augmented with polynomials. It is based on a closed-form expression for the interpolant, which reveals the mechanisms underlying these features, including the role of polynomials and RBFs in the interpolant, the approximation error, and the behavior of the cardinal functions near boundaries. Numerical examples are included for illustration. [ABSTRACT FROM AUTHOR]

This work provides a new mixed finite element method for the Brinkman problem over arbitrary convex quadrilateral meshes. The velocity is approximated by piecewise polynomial element space which is H ( div ) -nonconforming, and the pressure is approximated by piecewise constant. We give the convergence analysis of our element, and especially show the robustness with respect to the Darcy limit. Moreover, via a discrete de Rham complex, a higher-order approximation error term is obtained for incompressible flow. Numerical examples verify our theoretical findings. [ABSTRACT FROM AUTHOR]

Many applications of finite impulse response (FIR) digital filters impose strict format constraints on the filter coefficients. Such requirements increase the complexity of determining optimal designs for the problem at hand. We introduce a fast and efficient method, based on the computation of good nodes for polynomial interpolation and Euclidean lattice basis reduction. Experiments show that it returns quasi-optimal finite wordlength FIR filters; compared to previous approaches it also scales remarkably well (length 125 filters are treated in $<$ 9 s). It also proves useful for accelerating the determination of optimal finite wordlength FIR filters. [ABSTRACT FROM AUTHOR]

A fully implementable filtered polynomial approximation on spherical shells is considered. The method proposed is a quadrature-based version of a filtered polynomial approximation. The radial direction and the angular direction of the shells are treated separately with constructive filtered polynomial approximation. The approximation error with respect to the supremum norm is shown to decay algebraically for functions in suitable differentiability classes. Numerical experiments support the results. [ABSTRACT FROM AUTHOR]

A computationally simple method for generating reduced-order models that minimise the L2 norm of the approximation error while preserving a number of second-order information indices as well as the steady-state value of the step response, is presented. The method exploits the energy-conservation property peculiar to the Routh reduction method and the interpolation property of the L2-optimal approximation. Two examples taken from the relevant literature show that the suggested techniques may lead to approximations that are not worse than those afforded by popular more cumbersome techniques. [ABSTRACT FROM AUTHOR]

Orthogonal projection offers the optimal solution for many sampling-reconstruction problems in terms of the least square error. In the standard interpolation setting where the sampling is assumed to be ideal, however, the projection is impossible unless the interpolation kernel is related to the sinc function and the input is bandlimited. In this paper, we propose a notion of shifting kernel toward the orthogonal projection. For a given interpolation kernel, we formulate optimization problems whose solutions lead to shifted interpolations that, while still being interpolatory, are closest to the orthogonal projection in the sense of the minimax regret. The quality of interpolation is evaluated in terms of the average approximation error over input shift. For the standard linear interpolation, we obtain several values of optimal shift, dependent on a priori information on input signals. For evaluation, we apply the new shifted linear interpolations to a Gaussian signal, an ECG signal, a speech signal, a two-dimensional signal, and three natural images. Significant improvements are observed over the standard and the 0.21-shifted linear interpolation proposed early. [ABSTRACT FROM PUBLISHER]

Linear motion commands of computer numerical control (CNC) machine tools need to be smoothed at the transition corners in order to guarantee continuous and steady machining. However, because of the complex kinematic constraints, very few researches have devoted to developing analytical and high order continuous corner smoothing algorithms of five-axis tool paths, although it is important to guarantee both high calculation efficiency and good dynamic performance of five-axis CNC machining. This paper develops an analytical C 3 continuous corner smoothing algorithm of five-axis tool paths by locally inserting specially designed quintic micro splines into the transition corners of five-axis linear commands. C 3 continuity of the tool tip position and the tool orientation are guaranteed along the entire tool path. The maximal approximation errors of the tool tip position and the tool orientation are both constrained in the workpiece coordinate system. The synchronization of the tool tip position and tool orientation are mathematically guaranteed at the junctions of the linear and spline segments. The proposed corner smoothing algorithm can calculate all control points of the locally inserted tool tip position and tool orientation splines analytically without any iteration, which makes it very suitable to on-line calculation. Experiments on an in-house developed five-axis CNC platform verify that the maximal approximation errors of both tool tip position and tool orientation are constrained, and the proposed C 3 continuous corner smoothing algorithm has higher tracking accuracy and lower acceleration frequency content at higher frequencies than the C 2 continuous algorithm. [ABSTRACT FROM AUTHOR]

The linear canonical transform (LCT), which generalizes many classical transforms, has been shown to be a powerful tool for signal processing and optics. Sampling theory of the LCT for bandlimited signals has blossomed in recent years. However, in practice signals are never perfectly bandlimited, and in many cases measurement devices are nonideal. The objective of this paper is to develop a sampling theorem for the LCT from general measurements, which can provide a suitable and realistic model of sampling and approximation for real-world applications. We first describe a general class of approximation spaces for the LCT and provide a full characterization of their basis functions. Then, we propose a generalized sampling theorem for arbitrary measurement and approximation spaces associated with the LCT. Several properties of the proposed sampling theorem are also discussed. Furthermore, the approximation error is estimated. Finally, numerical results and several applications of the derived results are presented. [ABSTRACT FROM PUBLISHER]

State-of-the-art piecewise logarithmic converters employ nonuniform segments to reduce the variance of relative errors, particularly for small inputs. However, it is difficult to have an optimized algorithm to accurately choose the nonuniform segments for a required approximation error. In this brief, we present a relative error equal distribution (REED) algorithm that performs the nonuniform piecewise linear interpolation of logarithm. It is able to precisely set the nonuniform piecewise points so that the relative error of each segment is within an upper bound, and finally produce a flat relative error distribution. It can be applied to any number of segments, even if the number is not the power of 2. Experimental results show that our REED algorithm achieves over 70% reduction of average relative errors for the benchmark graphics application, compared to both the state-of-the-art uniform and nonuniform methods. Synthesis results show that our hardware resources are comparable to that of the state-of-the-art nonuniform methods. [ABSTRACT FROM AUTHOR]

To reduce the feedrate fluctuation in non-uniform rational B-spline (NURBS) interpolation caused by approximation errors of interpolation methods, a new NURBS interpolation method with minimal feedrate fluctuation for CNC machine tools is proposed to obtain the sampling curve parameter by solving a quartic equation with respect to the curve parameter increment according to the scheduled feedrate using Ferrari's formulas and Shengjin's formulas. Firstly, the second-order Taylor expansion is applied on the numerator and denominator in the NURBS representation separately with unknown curve parameter increment. Then, a quartic equation with respect to the curve parameter increment is formed and solved by Ferrari's formulas and Shengjin's formulas efficiently, which can achieve minimal feedrate fluctuation in real-time interpolation. In principle, the proposed method can totally eliminate the feedrate fluctuation for second-degree NURBS curves and can reduce it to a satisfied value for other high-degree NURBS curves. Finally, numerical simulations and experiments are conducted to verify the feasibility and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

A class of methods constructed to numerically approximate the solution of two-point singularly perturbed boundary value problems of the form ϵu'' + bu' + cu = f use exponentials to mimic exponential behavior of the solution in the boundary layer(s). We refer to them as exponentially fitted methods. Such methods are usually exact on polynomials of certain degree and some exponential functions. Shortly, they are exact on exponential sums. It is often possible that consistency of the method follows from the convergence of the interpolating function standing behind the method. Because of that, we consider the interpolation error for exponential sums. The main result of the paper is an error bound for interpolation by the exponential sum to the solution of the singularly perturbed problem that does not depend on perturbation parameter ϵ when ϵ is small with the respect to mesh width. The numerical experiment implies that the use of a dense mesh in the boundary layer for small meshwidth results in ϵ-uniform convergence. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we consider the approximation of a function by its interpolating multilinear spline and the approximation of its derivatives by the derivatives of the corresponding spline. We obtain the exact uniform approximation error on classes of functions with moduli of continuity bounded above by certain majorants. [Copyright &y& Elsevier]

Cutting speed is a key factor that influences machined surface quality and tool life in milling. To date, the study of its distribution over a machined surface has not been established. This paper presents a mathematical model to evaluate cutting speed on the machined surface in 3-axis ball nose milling. The approximation errors introduced by surface shape, step-over and CNC interpolation are analysed. The model is used to predict visible areas which have different colour intensities on finished surfaces in the machining of a wood-plastic composite. A good agreement is obtained between the prediction and experimental results. [ABSTRACT FROM AUTHOR]

The hardware computation of the logarithm function is required in several applications, ranging from signal and image processing to telecommunication systems. This brief shows that most of previous proposed logarithmic converters, based on piecewise linear approximations, suffer from large errors when dealing with fixed-point input values with many fractional bits, a situation often encountered in practical applications. Thus, this brief proposes a novel logarithmic converter, using nonuniform segmentation and piecewise linear approximation. A rigorous technique that allows computing the optimal segmentation and the coefficients values for a prescribed precision is described in this brief. For fixed-point input values, the proposed approach allows obtaining a sensibly lower error, for the same number of nonuniform segments, compared with previously published results. Implementation details and synthesis results in a 65-nm CMOS technology are also presented. [ABSTRACT FROM AUTHOR]

We present a method for real-time computation of clothoid coordinates that guarantees bounded approximation error over a wide range of clothoid parameters provided that the clothoid’s orientation change and length are bounded. It is shown that coordinates of clothoid with any parameters can be computed from those of a single clothoid (with fixed parameters), using appropriate geometrical transformations. A comprehensive analysis is given on how to determine a required set of clothoids and, based on this, how to sample a clothoid in a lookup table in order to achieve required approximation precision. The algorithm is computationally very efficient and therefore suitable for real-time path planning, as well as for other applications that benefit from fast clothoid computation. [ABSTRACT FROM PUBLISHER]