34 results about "Neyman pearson" patented technology

An outputs signal, v(t), is generated from a bioNEMs transducer and mixed with a reference signal and then filtered to generate a correlator output, r(t). The correlator output is detected to generate a signal u(t) and then determined whether the signal u(t) satisfies a predetermined threshold. If qualified, it is then decided whether the signal u(t) represents a predetermined type of interaction between a free ligand in a fluid in which the NEMS device is immersed and a receptor attached to the transducer. The threshold is the Neyman-Pearson criterion based on a predetermined probability of false detection, Pfa. The interaction may be binding of a free ligand to the receptor or releasing a bound ligand from the receptor by competitive binding with the free ligand. The step of detecting comprises detecting the envelope of the signal, r(t).

The invention discloses a physical layer authentication system security detection method which comprises the following steps: transmitting a first carrier signal by a transmitting end, and obtaining asecond carrier signal from the first carrier signal through a channel; receiving the second carrier signal by a hostile terminal, obtaining the first false alarm probability based on the second carrier signal and the first hypothesis test condition, and obtaining the first optimal threshold value when the first false alarm probability is less than or equal to the corresponding upper limit based on the Neyman-Pearson theory to determine the first detection probability; receiving the second carrier signal by the receiving end, obtaining the second false alarm probability based on the second carrier signal and the second hypothesis test condition, and obtianing the second optimal threshold value when the second false alarm probability is less than or equal to the corresponding upper limit respectively based on the Neyman-Pearson theory to determine the second detection probability; And the receiving end obtains a security authentication probability based on the first detection probability and the second detection probability to detect the security of the physical layer authentication system.

The invention relates to a repeating false target discriminating method based on angular glint. The method is characterized by establishing an angular glint statistical model according to a monopulse amplitude-comparing angle measurement method and performing correct discrimination by analyzing a difference between the azimuth error variances of an authentic target and a repeating false target and by using a Neyman-Pearson theorem and a generalized likelihood ratio test (GLRT) method, and comprises a step 1 of establishing angular glint statistical model according to the monopulse amplitude-comparing angle measurement method; a step 2 of estimating the parameter of angular observations in order to prepare for further target detection; a step 3 of acquiring a detection threshold according to a set false alarm probability, and then obtaining a detector output by using an echo signal in order to determine a threshold and finally obtain a detection result.

A ultra-wideband pulse signal two-step acquisition method based on the energy detection is divided into two main steps: first searching the energy window of the signal component, through the Neyman-Pearson rule, computing the detection probability of the DP energy window through the energy statistic characteristics of the UWB channel under the condition with certain false alarm probability; determining the precise position inside the energy window of DP. The invention overcomes the defect of low signal detection precision and larger operand of DP signal in the prior art, which not only advances the precision to acquire the signal but also reduces the cost of the hardware, increases the detecting efficiency.

The invention discloses a zero-speed detection method based on the Neiman-Pearson criterion. The method includes: receiving the measurement information output by the sensor when the footsteps are moving in the individual soldier navigation system in real time with a hand-held palm computer; according to the system sampling frequency and data transmission Determine the window function N of the speed; use the double hypothesis test theory to transform the zero-speed detection problem into a modeled mathematical problem, and obtain the zero-speed detection inequality under the Neiman-Pearson criterion; determine the output signal of the miniature inertial measurement unit sensor and the handheld computer The mathematical model of the received signal; obtain the joint probability density function of the output signal of the miniature inertial measurement unit sensor; use the maximum likelihood estimation value of the unknown signal element to replace the unknown element in the zero-speed detection inequality to obtain the extensive probability likelihood ratio inequality; the miniature The inertial measurement unit output data is substituted into the extensive probability-likelihood ratio inequality to detect the zero-velocity condition. The invention makes the problem of the detection method mathematized and modeled, and improves the detection precision.

The invention discloses a spectrum detection method based on the number of MTM-SVD adaptive sensor, and relates to the technical field of cognitive radio spectrum detection method. The MTM-SVD spectrum detection technology has the advantages that the prior information of a primary user is not needed, the detection and the reconstruction of signals submerged in colour noises are processed effectively, algorithm velocity is fast and the like, so the method of the invention can derive a threshold formula according to Neyman-Pearson standard based on MTM-SVD algorithm and determine the optimal number of real needed sensors. The receiving signals on each sensor are sampled, the characteristic spectrum of each sampled signal is calculated, and a new judgment amount TM(fi) is calculated according to the obtained characteristic spectrum; the new judgment amount TM(fi) is compared with a threshold th satisfying a false-alarm probability Pf to judge whether the spectrum is occupied or not. Compared with traditional energy detection, the method of the invention reduces the complexity of system while detecting the signal of the primary user correctively.

The invention provides a method for detecting SAR image change based on two-dimensional Gamma distribution, comprising the following steps: according to the input SAR image to be detected and reference image data, the parameters of the two-dimensional Gamma distribution is estimated by a moment estimation method; likelihood ratio statistics are formed by Neyman-Pearson criterion; based on the two-dimensional distribution, clutter suppression is carried out according to the dependency of the image data, thus gaining the image after clutter suppression; CFAR normalization is carried out on the image after clutter suppression; furthermore, global thresholds are set so as to binarize the image, thus obtaining an initial detection result; the binary image after detection is processed morphologically, counting-filtered, and target-clustered so as to further eliminate isolated false alarm points, thus gaining the final detection result. The method reaches higher detection rate based on the low false alarm point, and is applicable to detect artificial objects under various clutter environments, more especially under the strong clutter environments.

The invention provides a Neyman-Pearson criterion based SKIP mode rapidly selecting method. The method comprises steps that it is determined that prediction modes of a prediction unit are modeled as an "SKIP mode" and a "non-SKIP mode"; the rate distortion cost of the SKIP mode of a current coding unit is used as a decision-making feature; first four frames are counted and learned online, and when the optimal modes are respectively the SKIP mode and the non-SKIP mode, conditional probability distributions of the decision-making feature are obtained through non-parameter probability density estimation according to different quantitative parameters and different coding unit depths; and the SKIP modes of remaining frames are determined in advance by use of the Neyman-Pearson criterion according to statistic information learned online. On the basis of the Neyman-Pearson criterion, with false positive probability of the SKIP mode limited, false negative probability of the SKIP mode is reduced as much as possible, namely, while the rate distortion performance of coding is ensured, the coding speed is improved as much as possible.