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Table 2 Number of classification errors for all simulated examples and overlapping spike shapes

From: Automatic onlinespike sorting with singular value decomposition and fuzzy C-mean clustering

â„–

Example no.

Noise level

Number of overlapping spikes

False matches

N°.

%

1

2

3

4

1.

1

[0.05]

785

161

20.5

2.

[0.10]

769

146

19.0

3.

[0.15]

784

185

23.6

4.

[0.20]

796

165

20.7

5.

[0.25]

712

208

29.2

6.

[0.30]

846

250

29.6

7.

[0.35]

832

270

32.5

8.

[0.40]

741

270

36.4

9.

2

[0.05]

791

152

19.2

10.

[0.10]

826

167

20.2

11.

[0.15]

763

152

19.9

12.

[0.20]

811

301

37.1

13.

3

[0.05]

767

88

11.5

14.

[0.10]

810

131

16.2

15.

[0.15]

812

152

18.7

16.

[0.20]

790

287

36.3

17.

4

[0.05]

829

39

4.7

18

[0.10]

720

114

15.8

19.

[0.15]

809

209

25.8

20.

[0.20]

777

282

36.3

Average

789

186

23.7

  1. Noise level is represented in terms of its standard deviation relative to the peak amplitude of the spikes. All spike classes had a peak value of 1. The absolute number of false matching spikes is shown in column 3 as the outcome of our algorithm corresponding to the datasets containing overlapped spikes (column 2).