### Table 2. Simulation parameters Parameter Values Monitoring Period (s) 2 5 10 20

"... In PAGE 5: ... We decided to test the three Triggering functions under several limit values, several monitoring periods and several step sizes. All these variables are specified in Table2 . In addition to the 192 different combinations of these parameters we chose to perform all these simulations with two different traffic models: one with homogeneous connections and the other with heterogeneous connections.... ..."

### Table 1: Comparisons among different spectral methods and models in meeting the representation criteria. The yes and no roughly indicate whether or not they meet the corresponding criterion.

"... In PAGE 10: ... 2.5 Summary The evaluation results of all the spectral methods or models are summarized in Table1 . Of these methods or models, each has different advantages but none meets all the representation criteria.... In PAGE 32: ... Note that the representing data for discrete spikes are the same in schemes A and B. Table1 0A shows the data in scheme B for the spectra of the fluorescent sources, the mercury lamp and the sodium lamp, corresponding to the... In PAGE 33: ... Table1 0A: The data in scheme B for the spectra of the seven CIE standard fluorescent sources, a mercury lamp source and a sodium lamp source. These data are derived by evenly sampling 10 points of the functions reconstructed with the lowest 9 Fourier coefficients (given in Table 9A).... ..."

### Table 4: Weights of the linear model trained on the spectral-19 representation.

2006

"... In PAGE 7: ... A similar analysis can be performed on the features of the spectral representation. In brief, Table4 summarizes the weights associated to the spectral features when the LASSO is trained on the spectral features of the first 19 nucleotides. This table shows that, more than a general enrichment in particular nucleotides, the LASSO on the spectral representation detects the asymmetry of the guide sequences.... ..."

### Table 3: The cosmos representation: Support functions for Vase2-1 on the unit sphere.

1997

"... In PAGE 29: ... The Gauss map of the CSMPs is shown in part (c). The surface attributes stored by the coe cients in the support functions on the unit sphere for the vase are given (without the shape spectral functions) in Table3 . The support functions are de ned at points on the unit sphere as indicated in the table.... ..."

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### Table 1: Examples of spectral densities and correlation functions

"... In PAGE 15: ... 5 Applications In this section the idea of approximating stationary random functions with a fractional-rational spectral density by integral functionals of weakly correlated functions is applied to some practical important cases. Table1 gives some examples of spectral densities and correlation functions of stationary random functions which are widely used in engineering applications e.g.... ..."

### Table 1: Functionality and Representation Power

1993

Cited by 3

### Table 1: Categorization of Graphical Function Representations.

1995

"... In PAGE 4: ... 2. Graphical Function Representations Methods related to ordered BDDs for representing functions as graphs can be categorized as shown in Table1 .... ..."

Cited by 96

### Table 1. Variability and Spectral Properties

"... In PAGE 5: ... Statistical Properties of the Total Flux Density To parameterize the characteristic behavior of the ux variability a timescale of the variability from a rst-order structure function analysis, a variability in- dex measuring the peak-to-trough amplitude change, and an average radioband spectral index have been computed. These are included in Table1 based on UM- RAO observations during the period 1980.0{1996.... In PAGE 5: ...5 GHz and at 4.8 GHz, are tabulated in Table1 . All sources exhibited signi cant variability (V 0:1) at both frequencies, quantifying that radioband variability is a class property of BL Lacs.... ..."

### TABLE I Spectral representation based on mel-generalized cepstrum. (equation (5)).

1994

Cited by 7