Amino acids are quite important indices to indicate the growth status of oilseed rape under herbicide stress. Near infrared (NIR) spectroscopy combined with chemometrics was applied for fast determination of glutamic acid in oilseed rape leaves. The optimal spectral preprocessing method was obtained after comparing Savitzky-Golay smoothing, standard normal variate, multiplicative scatter corre...

ACI = Adjacent Channel Interferences APSK = Amplitude Phase Shift Key BER = Bit Error Rate DPD = Digital Predistortion DTH = Direct To Home EQ = EQualization FIR = Finite Impulse Response GW = Gate Way HPA = High Power Amplifier IBO = Input Back-Off IMUX = Input ISI = Inter-Symbol Interference L-TWTA = Linearized Travelling Wave Tube Amplifier LS = Least Squares OBO = Output Back-Off OMUX = Out...

Namyong Kim 155 In this paper, we introduce an escalator (ESC) algorithm based on the least squares (LS) criterion. The proposed algorithm is relatively insensitive to the eigenvalue spread ratio (ESR) of an input signal and has a faster convergence speed than the conventional ESC algorithms. This algorithm exploits the fast adaptation ability of least squares methods and the orthogonalization ...

Least squares (LS) problems are optimization problems in which the objective (error) function may be expressed as a sum of squares. Such problems have a natural relationship to distances in Euclidean geometry, and the solutions may be computed analytically using the tools of linear algebra. They can generally be interpreted and understood geometrically. They also have a statistical interpretati...

Least squares twin support vector machine (LS-TSVM) aims at resolving a pair of smaller-sized quadratic programming problems (QPPs) instead of a single large one as in the conventional least squares support vector machine (LS-SVM), which makes the learning speed of LS-TSVM faster than that of LS-SVM. However, same penalties are given to the negative samples when constructing the hyper-plane for...

The abnormal event detection problem is an important subject in real-time video surveillance. In this paper, we propose a novel online one-class classification algorithm, online least squares one-class support vector machine (online LS-OC-SVM), combined with its sparsified version (sparse online LS-OC-SVM). LS-OC-SVM extracts a hyperplane as an optimal description of training objects in a regul...

This paper presents novel adaptive space-time reduced-rank interference suppression least squares algorithms based on joint iterative optimization of parameter vectors. The proposed space-time reduced-rank scheme consists of a joint iterative optimization of a projection matrix that performs dimensionality reduction and an adaptive reduced-rank parameter vector that yields the symbol estimates....

We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible sequential nature) of training data arising in reinforcement learning we employ a subspace based variant of LS-SVM that sequentially processes the data and is hence especially suited for online learning. This approach is adapte...