Automatic segmentation of seismic signal with support of innovative filtering
The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coeffic...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hossa, Robert [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Schlagwörter: |
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| Umfang: |
11 |
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| Übergeordnetes Werk: |
Enthalten in: Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor - Ramakrishna, P.V. ELSEVIER, 2014transfer abstract, RMMS, Oxford |
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| Übergeordnetes Werk: |
volume:91 ; year:2017 ; pages:29-39 ; extent:11 |
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| DOI / URN: |
10.1016/j.ijrmms.2016.11.003 |
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| 245 | 1 | 0 | |a Automatic segmentation of seismic signal with support of innovative filtering |
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| 520 | |a The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. | ||
| 520 | |a The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. | ||
| 650 | 7 | |a Segmentation |2 Elsevier | |
| 650 | 7 | |a Reflection coefficients |2 Elsevier | |
| 650 | 7 | |a Seismic signal |2 Elsevier | |
| 650 | 7 | |a Underground mine |2 Elsevier | |
| 650 | 7 | |a Adaptive innovation filter |2 Elsevier | |
| 700 | 1 | |a Makowski, Ryszard |4 oth | |
| 700 | 1 | |a Zimroz, Radoslaw |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Pergamon |a Ramakrishna, P.V. ELSEVIER |t Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor |d 2014transfer abstract |d RMMS |g Oxford |w (DE-627)ELV017417449 |
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10.1016/j.ijrmms.2016.11.003 doi GBV00000000000049A.pica (DE-627)ELV040253759 (ELSEVIER)S1365-1609(16)30368-9 DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Hossa, Robert verfasserin aut Automatic segmentation of seismic signal with support of innovative filtering 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. Segmentation Elsevier Reflection coefficients Elsevier Seismic signal Elsevier Underground mine Elsevier Adaptive innovation filter Elsevier Makowski, Ryszard oth Zimroz, Radoslaw oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:29-39 extent:11 https://doi.org/10.1016/j.ijrmms.2016.11.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 29-39 11 045F 690 |
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10.1016/j.ijrmms.2016.11.003 doi GBV00000000000049A.pica (DE-627)ELV040253759 (ELSEVIER)S1365-1609(16)30368-9 DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Hossa, Robert verfasserin aut Automatic segmentation of seismic signal with support of innovative filtering 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. Segmentation Elsevier Reflection coefficients Elsevier Seismic signal Elsevier Underground mine Elsevier Adaptive innovation filter Elsevier Makowski, Ryszard oth Zimroz, Radoslaw oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:29-39 extent:11 https://doi.org/10.1016/j.ijrmms.2016.11.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 29-39 11 045F 690 |
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10.1016/j.ijrmms.2016.11.003 doi GBV00000000000049A.pica (DE-627)ELV040253759 (ELSEVIER)S1365-1609(16)30368-9 DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Hossa, Robert verfasserin aut Automatic segmentation of seismic signal with support of innovative filtering 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. Segmentation Elsevier Reflection coefficients Elsevier Seismic signal Elsevier Underground mine Elsevier Adaptive innovation filter Elsevier Makowski, Ryszard oth Zimroz, Radoslaw oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:29-39 extent:11 https://doi.org/10.1016/j.ijrmms.2016.11.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 29-39 11 045F 690 |
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10.1016/j.ijrmms.2016.11.003 doi GBV00000000000049A.pica (DE-627)ELV040253759 (ELSEVIER)S1365-1609(16)30368-9 DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Hossa, Robert verfasserin aut Automatic segmentation of seismic signal with support of innovative filtering 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. Segmentation Elsevier Reflection coefficients Elsevier Seismic signal Elsevier Underground mine Elsevier Adaptive innovation filter Elsevier Makowski, Ryszard oth Zimroz, Radoslaw oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:29-39 extent:11 https://doi.org/10.1016/j.ijrmms.2016.11.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 29-39 11 045F 690 |
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10.1016/j.ijrmms.2016.11.003 doi GBV00000000000049A.pica (DE-627)ELV040253759 (ELSEVIER)S1365-1609(16)30368-9 DE-627 ger DE-627 rakwb eng 690 550 690 DE-600 550 DE-600 670 VZ 333.7 610 VZ 43.12 bkl 43.13 bkl 44.13 bkl Hossa, Robert verfasserin aut Automatic segmentation of seismic signal with support of innovative filtering 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. Segmentation Elsevier Reflection coefficients Elsevier Seismic signal Elsevier Underground mine Elsevier Adaptive innovation filter Elsevier Makowski, Ryszard oth Zimroz, Radoslaw oth Enthalten in Pergamon Ramakrishna, P.V. ELSEVIER Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor 2014transfer abstract RMMS Oxford (DE-627)ELV017417449 volume:91 year:2017 pages:29-39 extent:11 https://doi.org/10.1016/j.ijrmms.2016.11.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO GBV_ILN_20 GBV_ILN_24 GBV_ILN_70 GBV_ILN_105 GBV_ILN_120 43.12 Umweltchemie VZ 43.13 Umwelttoxikologie VZ 44.13 Medizinische Ökologie VZ AR 91 2017 29-39 11 045F 690 |
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Enthalten in Synthesis, structural and luminescence properties of Ti co-doped ZnO/Zn2SiO4:Mn2+composite phosphor Oxford volume:91 year:2017 pages:29-39 extent:11 |
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Automatic segmentation of seismic signal with support of innovative filtering |
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The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. |
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The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. |
| abstract_unstemmed |
The paper presents a new algorithm for automatic segmentation of seismic signal. This segmentation relies on the observation of changes in the signal spectrum structure based exclusively on second-order signals statistics. The starting point of the proposed method are time-varying reflection coefficients of adaptive innovation filter. Schur's algorithm, performing the estimation of the reflection coefficients, is known as a fast, accurate and stable algorithm capable of quickly tracking the changes in signal statistics. Signal segmentation is a necessary stage for further processing of the signals, their interpretation, modelling or automatic classification. The issue of automatic segmentation is known in literature for its many applications (diagnostics of machinery, speech analysis, medicine etc.). There have also been a few proposals for segmentation of seismic signals. Unfortunately, segmentation of seismic signals is very difficult because of their variability. The purpose of the authors' work was to design an algorithm, which could be used in automatic processing of seismic signals in a deep underground copper mine. The paper presents the algorithm structure, defines its properties, specifies the values of parameters and presents the results of the effectiveness of the detection process. The obtained segmentation results are satisfactory. |
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Automatic segmentation of seismic signal with support of innovative filtering |
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