### TABLE 2. Circuitry of long-ranged fibers across most relevant electrode sites and their

in Statistical mechanics of neocortical interactions: Constraints on 40 Hz models of shortterm memory

1995

Cited by 6

### Table 1: Results of Canonical Correlation Analysis for Common Long-range Dependent Component plus White Noise

1997

Cited by 3

### Table 2: Results of Canonical Correlation Analysis for Common Long-range Dependent Component plus MA Noise

1997

Cited by 3

### Table 3: Results of Canonical Correlation Analysis for Common Long-range Dependent Component plus AR and MA Noise

1997

Cited by 3

### Table 1: Di erences between the short-range dependent processes and the long-range dependent processes

1996

Cited by 2

### Table 1. The lowest frequencies and their amplitudes for long-range longitudinal wake function of the LOLA structure.

2004

"... In PAGE 7: ...7 by dashed line. The values are obtained using the Prony-Pisarenko algorithm [7] and are given in Table1 . The Prony-Pisarenko algorithm is a method to fit a set of decaying oscillation characterized by amplitudes, phases and damping constants to a given curve or data set and is used in our paper as alternative to the discrete Fourier transform.... ..."

### Table 2. The lowest frequencies and their amplitudes for long-range transverse wake function of the LOLA structure.

2004

### Table 4. The lowest frequencies and their amplitudes for long-range transverse wake function of 3rd harmonic section.

2004

### Table IX: characteristics of medium- and long-range systems other than UMTS

2005

### Table 2: Estimated Long-range Dependence Parameter for Daily Volatilities of 100 Ran- domly Selected S amp;P 500 Companies

2000

"... In PAGE 4: ... Any company having fewer than 3000 daily returns was replaced by another random draw within the same decile. The selected companies are given in Table2 , identified by their tick symbols. We test for long-range dependence in daily stock volatilities by estimating the fractional integrating parameter d for the logarithm of squared returns of selected companies.... In PAGE 6: ...he standard deviation of the GPH estimates, 0.0538 compared to 0.0913. We use these two methods to estimate d for the volatilities of S amp;P 500 companies. The second column of Table2 shows the estimates of d for the 100 selected companies using the spectral regression method. The mean and median of dGPH are 0.... In PAGE 7: ...Table2 shows the estimates of d for the 100 selected companies using QMLE. The QMLE estimates are consistent with those obtained using GPH, again in- dicating strong evidence of significant long-range dependence in the majority of sampled companies.... ..."

Cited by 3