Abstract: Provided is a method for detecting a biomarker indicating states of a target biological system based on data acquired by measuring the target biological system. The method includes the steps of: preparing a reference dataset based on data acquired from one or more reference biological systems; generating a target dataset by adding, to the reference dataset, target biological data acquired from the target biological system; acquiring first correlation coefficients between a plurality of factor items in the reference dataset; acquiring second correlation coefficients between the plurality of factor items in the target dataset; acquiring difference correlation coefficients that are differences between the first correlation coefficients and the second correlation coefficients; acquiring indexes respectively for the plurality of factor items based on the difference correlation coefficients; and selecting the biomarker based on the indexes.

Abstract: A neural network device narrows down, from among respective time segments from when a spike is received to when a next spike is received, a candidate of a time segment including a firing timing of a spiking neuron, a membrane potential of the spiking neuron during a period from when a spike is received to when a next spike is received being represented by a monotonic function of time, a firing condition of the spiking neuron being represented by a comparison between the membrane potential and a threshold.

Abstract: A machine learning device includes: an input unit that acquires input data; an intermediate calculation unit that performs calculation on the input data a plurality of times; a weighting unit that performs weighting on an output of the intermediate calculation means for each of the plurality of times; an output unit that outputs output data based on a result of the weighting by the weighting means; and a learning unit that performs learning of a weight obtained by the weighting by the weighting means.

Abstract: A spiking neural network system includes: a time-based spiking neural network; and a learning processing unit that causes learning of the spiking neural network to be performed by supervised learning using a cost function, the cost function using a regularization term relating to a firing time of a neuron in the spiking neural network.

Abstract: The present invention provides a device, method, and program for detection of a biomarker candidate that may be used in a diagnosis of a pre-disease state indicating a transition from a healthy state to a disease state. Biological samples are collected from a subject to be measured at different times. Statistical data is obtained by aggregating measurement data obtained in measurement on collected biological samples. Thereafter, a process of obtaining high-throughput data (s1), a process of choosing differential biological molecules (s2), a process of clustering (s3), a process of choosing a DNB candidate (s4), and a process of identifying a DNB by significance analysis (s5) are carried out.

Abstract: A neural network device includes: a neuron model unit configured as a non-leaky integrate-and-fire spiking neuron and a spiking neuron with which a postsynaptic current is represented using a step function, the neuron model unit being fired once at most in one process of a neural network to indicate an output of the neural model unit itself at firing timing; and a transfer processing unit that transfers information between the neuron model unit.

Abstract: A data processing apparatus is configured to solve a specific problem using a simple hardware. The data processing apparatus comprises a state data processing unit configured to iterate update of state data by a predetermined time evolutional process, a cost evaluation unit configured to evaluate a cost function for current state data, and an error calculation unit configured to calculate error values relating to amplitude homogeneity of the current state data, wherein the state data processing unit performs the time evolutional process on the state data to update the current state data based on the cost function and the error values which are calculated by the error calculation unit.

Abstract: Provided is a method for detecting a biomarker indicating states of a target biological system based on data acquired by measuring the target biological system. The method includes the steps of: preparing a reference dataset based on data acquired from one or more reference biological systems; generating a target dataset by adding, to the reference dataset, target biological data acquired from the target biological system; acquiring first correlation coefficients between a plurality of factor items in the reference dataset; acquiring second correlation coefficients between the plurality of factor items in the target dataset; acquiring difference correlation coefficients that are differences between the first correlation coefficients and the second correlation coefficients; acquiring indexes respectively for the plurality of factor items based on the difference correlation coefficients; and selecting the biomarker based on the indexes.

Abstract: The invention provides a detection device, method, and program capable of highly accurately detecting a pre-disease state that indicates a precursor to a state transition from a healthy state to a disease state. The following processes are carried out: a process of obtaining measured data on genes, proteins, etc. related to a biological object as high-throughput data (s1), a process of selecting differential biological molecules (s2), a process of calculating the SNE of a local network (s3), a process of selecting a biomarker candidate (s4), a process of calculating an average SNE across the entire network (s5), and a process of determining and detecting whether or not the system is in a pre-disease state (s6).

Abstract: The invention provides a detection device, method, and program capable of highly accurately detecting a pre-disease state that indicates a precursor to a state transition from a healthy state to a disease state. The following processes are carried out: a process of obtaining measured data on genes, proteins, etc. related to a biological object as high-throughput data (s1), a process of selecting differential biological molecules (s2), a process of calculating the SNE of a local network (s3), a process of selecting a biomarker candidate (s4), a process of calculating an average SNE across the entire network (s5), and a process of determining and detecting whether or not the system is in a pre-disease state (s6).

Abstract: The present invention provides a device, method, and program for detection of a biomarker candidate that may be used in a diagnosis of a pre-disease state indicating a transition from a healthy state to a disease state. Biological samples are collected from a subject to be measured at different times. Statistical data is obtained by aggregating measurement data obtained in measurement on collected biological samples. Thereafter, a process of obtaining high-throughput data (s1), a process of choosing differential biological molecules (s2), a process of clustering (s3), a process of choosing a DNB candidate (s4), and a process of identifying a DNB by significance analysis (s5) are carried out.

Abstract: There is provided a data conversion method based on negative ?-map suited for an A/D converter or chaos generator, that is adapted to an integrated circuit and capable of providing stable operation of the circuit. The data conversion method based on negative ?-map includes a discrete time integrator 1 having an amplification coefficient s and a damping factor ?, a quantizer 2 connected in series to the discrete time integrator 1, and a feedback circuit connected from an output of the quantizer 2 to an input of the discrete time integrator 1.

Abstract: There is provided a data conversion method based on ?-map suited for an A/D converter or chaos generator, that is adapted to an integrated circuit and capable of providing stable operation of the circuit. The data conversion method based on scale-adjusted ?-map includes a discrete time integrator 1 having an amplification coefficient s(1??) and a damping factor ?, a quantizer 2connected in series to the discrete time integrator 1, and a feedback circuit 3 connected from an output of the quantizer 2 to an input of the discrete time integrator 1.

Abstract: There is provided a multi-screw chaotic oscillator circuit with simple configuration, that can use various multi-hysteresis VCCS characteristics and generate a variety of multi-screw attractors. The multi-screw chaotic oscillator circuit comprises: a linear two-port VCCS circuit 1 consisting of a set of linear VCCS circuits G1 and G2; a multi-hysteresis two-port VCCS circuit 2 consisting of a set of multi-hysteresis VCCS circuits MH1 and MH2 having multi-hysteresis characteristic; and capacitors C1 and C2 connected to each end of a circuit configured by parallel-connecting the linear two-port VCCS circuit 1 and the multi-hysteresis two-port VCCS circuit 2.

Abstract: A multi-hysteresis voltage controlled current source system having a variety of multi-hysteresis characteristics is provided. In the multi-hysteresis voltage controlled current source system, single-hysteresis voltage controlled current source circuits 21, 22, . . . 2N as fundamental components are connected in parallel, and a differential input voltage vid is applied to the single-hysteresis voltage controlled current source circuits 21, 22, . . . 2N, so that a plurality of discrete values of current can be output based on the single-hysteresis voltage controlled current source circuits 21, 22, . . . 2N.

Abstract: There is provided a mechanism for generating random numbers following the normal distribution which does not generate a sequence correlation. The mechanism for generating random numbers following the normal distribution includes: a random recurrence plot generating mechanism 1 for generating random recurrence plots; and a recurrence plot-time series converting mechanism 4 for converting the random recurrence plots from the random recurrence plot generating unit 1 into time series, wherein Gaussian random numbers are generated by the recurrence plot-time series converting mechanism 4.

Abstract: There is provided a data conversion method based on negative ?-map suited for an A/D converter or chaos generator, that is adapted to an integrated circuit and capable of providing stable operation of the circuit. The data conversion method based on negative ?-map includes a discrete time integrator 1 having an amplification coefficient s and a damping factor ?, a quantizer 2 connected in series to the discrete time integrator 1, and a feedback circuit connected from an output of the quantizer 2 to an input of the discrete time integrator 1.

Abstract: There is provided a data conversion method based on ?-map suited for an A/D converter or chaos generator, that is adapted to an integrated circuit and capable of providing stable operation of the circuit. The data conversion method based on scale-adjusted ?-map includes a discrete time integrator 1 having an amplification coefficient s(1??) and a damping factor ?, a quantizer 2 connected in series to the discrete time integrator 1, and a feedback circuit 3 connected from an output of the quantizer 2 to an input of the discrete time integrator 1.

Abstract: There is provided a multi-screw chaotic oscillator circuit with simple configuration, that can use various multi-hysteresis VCCS characteristics and generate a variety of multi-screw attractors. The multi-screw chaotic oscillator circuit comprises: a linear two-port VCCS circuit 1 consisting of a set of linear VCCS circuits G1 and G2; a multi-hysteresis two-port VCCS circuit 2 consisting of a set of multi-hysteresis VCCS circuits MH1 and MH2 having multi-hysteresis characteristic; and capacitors C1 and C2 connected to each end of a circuit configured by parallel-connecting the linear two-port VCCS circuit 1 and the multi-hysteresis two-port VCCS circuit 2.

Abstract: A multi-hysteresis voltage controlled current source system having a variety of multi-hysteresis characteristics is provided. In the multi-hysteresis voltage controlled current source system, single-hysteresis voltage controlled current source circuits 21, 22, . . . 2N as fundamental components are connected in parallel, and a differential input voltage vid is applied to the single-hysteresis voltage controlled current source circuits 21, 22, . . . 2N, so that a plurality of discrete values of current can be output based on the single-hysteresis voltage controlled current source circuits 21, 22, . . . 2N.