The I/O transform of a chemical sensor
A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allow...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Katta, Nalin [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
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| Schlagwörter: |
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| Umfang: |
12 |
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| Übergeordnetes Werk: |
Enthalten in: Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery - Borgès Da Silva, Virginie ELSEVIER, 2018, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:232 ; year:2016 ; pages:357-368 ; extent:12 |
| Links: |
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| DOI / URN: |
10.1016/j.snb.2016.03.019 |
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| 520 | |a A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. | ||
| 520 | |a A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. | ||
| 650 | 7 | |a Chemical sensors |2 Elsevier | |
| 650 | 7 | |a Impulse response |2 Elsevier | |
| 650 | 7 | |a Signal processing |2 Elsevier | |
| 650 | 7 | |a Sensor drift |2 Elsevier | |
| 650 | 7 | |a Array replacement |2 Elsevier | |
| 650 | 7 | |a Sensor arrays |2 Elsevier | |
| 700 | 1 | |a Meier, Douglas C. |4 oth | |
| 700 | 1 | |a Benkstein, Kurt D. |4 oth | |
| 700 | 1 | |a Semancik, Steve |4 oth | |
| 700 | 1 | |a Raman, Baranidharan |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Borgès Da Silva, Virginie ELSEVIER |t Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery |d 2018 |g Amsterdam [u.a.] |w (DE-627)ELV001079875 |
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10.1016/j.snb.2016.03.019 doi GBVA2016014000030.pica (DE-627)ELV01425395X (ELSEVIER)S0925-4005(16)30313-6 DE-627 ger DE-627 rakwb eng 530 620 530 DE-600 620 DE-600 610 VZ 44.91 bkl Katta, Nalin verfasserin aut The I/O transform of a chemical sensor 2016transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. Chemical sensors Elsevier Impulse response Elsevier Signal processing Elsevier Sensor drift Elsevier Array replacement Elsevier Sensor arrays Elsevier Meier, Douglas C. oth Benkstein, Kurt D. oth Semancik, Steve oth Raman, Baranidharan oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:232 year:2016 pages:357-368 extent:12 https://doi.org/10.1016/j.snb.2016.03.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 232 2016 357-368 12 045F 530 |
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10.1016/j.snb.2016.03.019 doi GBVA2016014000030.pica (DE-627)ELV01425395X (ELSEVIER)S0925-4005(16)30313-6 DE-627 ger DE-627 rakwb eng 530 620 530 DE-600 620 DE-600 610 VZ 44.91 bkl Katta, Nalin verfasserin aut The I/O transform of a chemical sensor 2016transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. Chemical sensors Elsevier Impulse response Elsevier Signal processing Elsevier Sensor drift Elsevier Array replacement Elsevier Sensor arrays Elsevier Meier, Douglas C. oth Benkstein, Kurt D. oth Semancik, Steve oth Raman, Baranidharan oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:232 year:2016 pages:357-368 extent:12 https://doi.org/10.1016/j.snb.2016.03.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 232 2016 357-368 12 045F 530 |
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10.1016/j.snb.2016.03.019 doi GBVA2016014000030.pica (DE-627)ELV01425395X (ELSEVIER)S0925-4005(16)30313-6 DE-627 ger DE-627 rakwb eng 530 620 530 DE-600 620 DE-600 610 VZ 44.91 bkl Katta, Nalin verfasserin aut The I/O transform of a chemical sensor 2016transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. Chemical sensors Elsevier Impulse response Elsevier Signal processing Elsevier Sensor drift Elsevier Array replacement Elsevier Sensor arrays Elsevier Meier, Douglas C. oth Benkstein, Kurt D. oth Semancik, Steve oth Raman, Baranidharan oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:232 year:2016 pages:357-368 extent:12 https://doi.org/10.1016/j.snb.2016.03.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 232 2016 357-368 12 045F 530 |
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10.1016/j.snb.2016.03.019 doi GBVA2016014000030.pica (DE-627)ELV01425395X (ELSEVIER)S0925-4005(16)30313-6 DE-627 ger DE-627 rakwb eng 530 620 530 DE-600 620 DE-600 610 VZ 44.91 bkl Katta, Nalin verfasserin aut The I/O transform of a chemical sensor 2016transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. Chemical sensors Elsevier Impulse response Elsevier Signal processing Elsevier Sensor drift Elsevier Array replacement Elsevier Sensor arrays Elsevier Meier, Douglas C. oth Benkstein, Kurt D. oth Semancik, Steve oth Raman, Baranidharan oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:232 year:2016 pages:357-368 extent:12 https://doi.org/10.1016/j.snb.2016.03.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 232 2016 357-368 12 045F 530 |
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10.1016/j.snb.2016.03.019 doi GBVA2016014000030.pica (DE-627)ELV01425395X (ELSEVIER)S0925-4005(16)30313-6 DE-627 ger DE-627 rakwb eng 530 620 530 DE-600 620 DE-600 610 VZ 44.91 bkl Katta, Nalin verfasserin aut The I/O transform of a chemical sensor 2016transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. Chemical sensors Elsevier Impulse response Elsevier Signal processing Elsevier Sensor drift Elsevier Array replacement Elsevier Sensor arrays Elsevier Meier, Douglas C. oth Benkstein, Kurt D. oth Semancik, Steve oth Raman, Baranidharan oth Enthalten in Elsevier Science Borgès Da Silva, Virginie ELSEVIER Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery 2018 Amsterdam [u.a.] (DE-627)ELV001079875 volume:232 year:2016 pages:357-368 extent:12 https://doi.org/10.1016/j.snb.2016.03.019 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.91 Psychiatrie Psychopathologie VZ AR 232 2016 357-368 12 045F 530 |
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Enthalten in Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery Amsterdam [u.a.] volume:232 year:2016 pages:357-368 extent:12 |
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Enthalten in Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery Amsterdam [u.a.] volume:232 year:2016 pages:357-368 extent:12 |
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Association between binge eating disorder and psychiatric comorbidity profiles in patients with obesity seeking bariatric surgery |
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The I/O transform of a chemical sensor |
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A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. |
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A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. |
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A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. |
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