A double sampling circuit to eliminating fixed pattern noise(FPN) in CMOS image sensor (CIS) is presented. Double sampling is implemented by column switch capacitor amplifier directly, and offset compensation is added...A double sampling circuit to eliminating fixed pattern noise(FPN) in CMOS image sensor (CIS) is presented. Double sampling is implemented by column switch capacitor amplifier directly, and offset compensation is added to the amplifier to suppress column FPN. The amplifier is embedded in a 64×64 CIS and successfully fabricated with chartered 0.35 μm process. Theory analysis and circuit simulation indicate that FPN can be suppressed from millivolt to microvolt. Test results show that FPN is smaller than one least-significant bit of 8 bit ADC. FPN is reduced to an acceptable level with double sampling technique implemented with switch capacitor amplifier.展开更多
A low cost of die area and power consumption CMOS image sensor readout circuit with fixed pattern noise(FPN) cancellation is proposed.By using only one coupling capacitor and switch in the double FPN cancelling correl...A low cost of die area and power consumption CMOS image sensor readout circuit with fixed pattern noise(FPN) cancellation is proposed.By using only one coupling capacitor and switch in the double FPN cancelling correlative double sampling(CDS),pixel FPN is cancelled and column FPN is stored and eliminated by the sampleand-hold operation of digitally programmable gain amplifier(DPGA).The bandwidth balance technology based on operational amplifier(op-amp) sharing is also introduced to decrease the power dissi...展开更多
It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm.However,high utility quantitative freq...It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm.However,high utility quantitative frequent pattern mining algorithms in the field of data mining still suffer from the problems of low time-memory performance and are not easy to scale up.In the context of such needs,we propose a related degree-based frequent pattern mining algorithm,named Related High Utility Quantitative Item set Mining(RHUQI-Miner),to enable the effective mining of railway fault data.The algorithm constructs the item-related degree structure of fault data and gives a pruning optimization strategy to find frequent patterns with higher related degrees,reducing redundancy and invalid frequent patterns.Subsequently,it uses the fixed pattern length strategy to modify the utility information of the item in the mining process so that the algorithm can control the length of the output frequent pattern according to the actual data situation and further improve the performance and practicability of the algorithm.The experimental results on the real fault dataset show that RHUQI-Miner can effectively reduce the time and memory consumption in the mining process,thus providing data support for differentiated and precise maintenance strategies.展开更多
基金Supported by National Natural Science Foundation of China (No.60576025).
文摘A double sampling circuit to eliminating fixed pattern noise(FPN) in CMOS image sensor (CIS) is presented. Double sampling is implemented by column switch capacitor amplifier directly, and offset compensation is added to the amplifier to suppress column FPN. The amplifier is embedded in a 64×64 CIS and successfully fabricated with chartered 0.35 μm process. Theory analysis and circuit simulation indicate that FPN can be suppressed from millivolt to microvolt. Test results show that FPN is smaller than one least-significant bit of 8 bit ADC. FPN is reduced to an acceptable level with double sampling technique implemented with switch capacitor amplifier.
基金Supported by National Natural Science Foundation of China (No.60806010,No.60976030)Tianjin Innovation Special Funds for Science and Technology (No.05FZZDGX00200)
文摘A low cost of die area and power consumption CMOS image sensor readout circuit with fixed pattern noise(FPN) cancellation is proposed.By using only one coupling capacitor and switch in the double FPN cancelling correlative double sampling(CDS),pixel FPN is cancelled and column FPN is stored and eliminated by the sampleand-hold operation of digitally programmable gain amplifier(DPGA).The bandwidth balance technology based on operational amplifier(op-amp) sharing is also introduced to decrease the power dissi...
基金supported by the Research on Key Technologies and Typical Applications of Big Data in Railway Production and Operation(P2023S006)the Fundamental Research Funds for the Central Universities(2022JBZY023).
文摘It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm.However,high utility quantitative frequent pattern mining algorithms in the field of data mining still suffer from the problems of low time-memory performance and are not easy to scale up.In the context of such needs,we propose a related degree-based frequent pattern mining algorithm,named Related High Utility Quantitative Item set Mining(RHUQI-Miner),to enable the effective mining of railway fault data.The algorithm constructs the item-related degree structure of fault data and gives a pruning optimization strategy to find frequent patterns with higher related degrees,reducing redundancy and invalid frequent patterns.Subsequently,it uses the fixed pattern length strategy to modify the utility information of the item in the mining process so that the algorithm can control the length of the output frequent pattern according to the actual data situation and further improve the performance and practicability of the algorithm.The experimental results on the real fault dataset show that RHUQI-Miner can effectively reduce the time and memory consumption in the mining process,thus providing data support for differentiated and precise maintenance strategies.
