762results about How to "Reduce correlation" patented technology

Structural parameters of a specimen are determined by fitting models of the response of the specimen to measurements collected by different measurement techniques in a combined analysis. Models of the response of the specimen to at least two different measurement technologies share at least one common geometric parameter. In some embodiments, a model building and analysis engine performs x-ray and optical analyses wherein at least one common parameter is coupled during the analysis. The fitting of the response models to measured data can be done sequentially, in parallel, or by a combination of sequential and parallel analyses. In a further aspect, the structure of the response models is altered based on the quality of the fit between the models and the corresponding measurement data. For example, a geometric model of the specimen is restructured based on the fit between the response models and corresponding measurement data.

Methods and systems for performing measurements based on a measurement model integrating a metrology-based target model with a process-based target model. Systems employing integrated measurement models may be used to measure structural and material characteristics of one or more targets and may also be used to measure process parameter values. A process-based target model may be integrated with a metrology-based target model in a number of different ways. In some examples, constraints on ranges of values of metrology model parameters are determined based on the process-based target model. In some other examples, the integrated measurement model includes the metrology-based target model constrained by the process-based target model. In some other examples, one or more metrology model parameters are expressed in terms of other metrology model parameters based on the process model. In some other examples, process parameters are substituted into the metrology model.

A wireless broadband communications system that can transmit signals over communications links with multiple modes of diversity, thereby allowing signals having very low correlation to propagate over the link along multiple orthogonal paths. The system can be implemented as a non-line-of-sight (NLOS) system or a line-of-sight (LOS) system. The NLOS system employs orthogonal frequency division modulation (OFDM) waveforms to reduce multi-path interference and frequency selective fading, adaptive modulation to assure high data rates in the presence of channel variability, and spectrum management to achieve increased data throughput and link availability. The LOS system employs space-time coding and spatial and polarization diversity to minimize ground bounce nulls. The system achieves levels of link availability, data throughput, and system performance that have heretofore been unattainable in wireless broadband communications systems.

A device for generating a binaural signal based on a multi-channel signal representing a plurality of channels and intended for reproduction by a speaker configuration having a virtual sound source position associated to each channel, is described. It includes a correlation reducer for differently processing, and thereby reducing a correlation between, at least one of a left and a right channel of the plurality of channels, a front and a rear channel of the plurality of channels, and a center and a non-center channel of the plurality of channels, in order to obtain an inter-similarity reduced set of channels; a plurality of directional filters, a first mixer for mixing outputs of the directional filters modeling the acoustic transmission to the first ear canal of the listener, and a second mixer for mixing outputs of the directional filters modeling the acoustic transmission to the second ear canal of the listener. According to another aspect, a center level reduction for forming the downmix for a room processor is performed. According to even another aspect, an inter-similarity decreasing set of head-related transfer functions is formed.

To provide a secure cryptographic device such as an IC card which can endure TA (Timing Attack), DPA (Differential Power Analysis), SPA (Simple Power Analysis), or the like as an attaching method of presuming secret information held therein, when the secret information held in the card or another information which is used in the secret information or an arithmetic operation using such secret information when such an arithmetic operation is performed is shown by a plurality of expressing methods and the arithmetic operation is performed, thereby making an arithmetic operation processing method different each time the arithmetic operation is performed and making each of an arithmetic operation time, an intensity of a generated electromagnetic wave, and a current consumption different.

An apparatus and method of reproducing a virtual sound of two channels which adaptively reproduces a 2-channel stereo sound signal reproduced through a recording medium such as DVD, CD, or MP3 player etc., based on a listener's position. The method includes sensing a listener's position and recognizing distance and angle information about the listener's position, determining output gain values and delay values of two speakers based on the distance and angle information about the sensed listener's position and selecting localization filter coefficients in a predetermined table, and updating filter coefficients of a localization filter based on the selected localization filter coefficients and adjusting output levels and time delays of the two speakers from the determined gain values and delay values.

The invention relates to a color image encryption method based on a chaos sequence and a hyper-chaos system. The color image encryption method mainly comprises the following steps: an original color image is subjected to bit level united scrambling to obtain a scrambled image; the scrambled image is decomposed into three primary color components, that is R, G and B, and the hyper-chaos system is used for generating an encryption matrix which is used for encrypting the scrambled image; all pixel values of the three primary color components of the scrambled image are changed by utilizing the encryption matrix in combination with plaintext information and information of the three primary color components, united diffusion is conducted to obtain the three primary color components of the image after the united diffusion, and therefore a final encrypted image is obtained. By means of the color image encryption method, a secret key space is greatly enlarged, the safety, the encryption effect and the sensitivity of a secret key are higher, the anti-attack ability is stronger, and hardware implementation is easier.

When first and second housings are in an open state, first and second switches are electrically opened, and thus, a first antenna element and a ground conductor operate as a first dipole antenna, and a second antenna element and the ground conductor operate as a second dipole antenna with isolation from the first dipole antenna by the slit. When the first and second housings are in the closed state, the first and second switches are electrically closed, and thus, the first antenna element operates as a first inverted F antenna on the ground conductor, and the second antenna element operates as a second inverted F antenna on the ground conductor with isolation from the first inverted F antenna by the slit.

Structural parameters of a specimen are determined by fitting models of the response of the specimen to measurements collected by different measurement techniques in a combined analysis. X-ray measurement data of a specimen is analyzed to determine at least one specimen parameter value that is treated as a constant in a combined analysis of both optical measurements and x-ray measurements of the specimen. For example, a particular structural property or a particular material property, such as an elemental composition of the specimen, is determined based on x-ray measurement data. The parameter(s) determined from the x-ray measurement data are treated as constants in a subsequent, combined analysis of both optical measurements and x-ray measurements of the specimen. In a further aspect, the structure of the response models is altered based on the quality of the fit between the models and the corresponding measurement data.

An antenna apparatus includes a first feeding point and a second feeding point provided at respective positions on an antenna element. The antenna element is excited through the first and second feeding points simultaneously so as to operate as a first antenna portion and a second antenna portion simultaneously, the first antenna portion and the second antenna portion correspond to the first and second feeding points, respectively. The antenna element further includes, between the first and second feeding points, an electromagnetic coupling adjuster for making an amount of isolation between the first and second antenna portions.

An apparatus to process m-channel audio input signals to produce n channel output signals, and n is less than m. This apparatus includes a first filter unit to reduce a correlation between at least two channel audio input signals among the m-channel audio input signals, a virtual sound source generation unit to transform the at least two channel audio input signals output from the first filter unit into virtual sound sources at predetermined positions around a listener position, and an output controller to control channel audio input signals other than the at least two channel audio input signals among the m-channel audio input signals based on gains and delays of the at least two channel audio input signal output from the virtual sound source generation unit. Even when the m-channel audio input signals are reproduced through 2 channels, a surround effect provided by an m-channel speaker system can be obtained. In addition, a localization of a sound is improved, and a presence is formed. Thus, an enhanced surround sound is provided to a listener.

The invention provides a bivariate nonlocal average filtering de-noising method for an X-ray image. The method is characterized by comprising the following steps: 1) a selecting method of a fuzzy de-noising window; and 2) a bivariate fuzzy adaptive nonlocal average filtering algorithm. The method has the beneficial effects that in order to preferably remove the influence caused by the unknown quantum noise existing in an industrial X-ray scan image, the invention provides the bivariate nonlocal fuzzy adaptive non-linear average filtering de-noising method for the X-ray image, in the method, a quantum noise model which is hard to process is converted into a common white gaussian noise model, the size of a window of a filter is selected by virtue of fuzzy computation, and a relevant weight matrix enabling an error function to be minimum is searched. A particle swarm optimization filtering parameter is introduced in the method, so that the weight matrix can be locally rebuilt, the influence of the local relevancy on the sample data can be reduced, the algorithm convergence rate can be improved, and the de-noising speed and precision for the industrial X-ray scan image can be improved, so that the method is suitable for processing the X-ray scan image with an uncertain noise model.

The invention relates to an image encryption method and an image decryption method with visual security and data security based on compressed sensing. The image encryption method comprises the steps of: firstly, utilizing an SHA 256 hash function to obtain a 256-bit hash value of a plaintext image as an image secret key, and calculating initial numerical values of one-dimensional skew tent chaotic mapping and zigzag scrambling; carrying out sparse processing on the plaintext image, and carrying out zigzag scrambling on a coefficient matrix; and then utilizing the one-dimensional skew tent chaotic mapping to generate a measurement matrix, measuring and quantifying a scrambling matrix to obtain a compressed and encrypted image, and embedding the image into a carrier image with visual significance to obtain a final ciphertext image with visual significance. The image encryption method realizes the visual security and data security of the plaintext image, has large secret key space, is highly sensitive to plaintext, has higher capacity of resisting brute-force attack, chosen-plaintext attack and known-plaintext attack, does not need an additional storage space, and can transmit and store the ciphertext image quickly and effectively.

The invention discloses a ground electromagnetic prospecting method based on an SPSP (Spread Spectrum) coding technology and a detection system thereof. The ground electromagnetic prospecting method based on the SPSP coding technology comprises the following steps of: supplying a current signal hopping according to a certain coded sequence to underground by a sending electrode, and using the current signal as a manual excitation source; receiving an electromagnetic field response message by a receiver, and meanwhile, synchronously recording the sent current signal and the geoelectrical response message of the position where the receiver is located by the receiver; and obtaining ground system response comprising the geoelectrical resistivity through a correlated identification method, and finally obtaining the distribution characteristics of the geoelectrical resistivity. According to the detection system applying the ground electromagnetic prospecting method disclosed by the invention, a sine-wave or square-wave signal in unipolarity or bipolarity in the whole preset frequency range can be sent by a transmitter, a sending sequence can hop according to a preset frequency pattern, and uncorrelated noise can be removed through a correlated identification detection method.

The invention discloses a collision avoidance planning method for mobile robots based on deep reinforcement learning in a dynamic environment, and belongs to the technical field of mobile robot navigation. The method of the invention includes the following steps of: collecting raw data through a laser rangefinder, processing the raw data as input of a neural network, and building an LSTM neural network; through an A3C algorithm, outputting corresponding parameters by the neural network, and processing the corresponding parameters to obtain the action of each step of the robot. The scheme of the invention does not need to model the environment, is more suitable for an unknown obstacle environment, adopts an actor-critic framework and a temporal difference algorithm, is more suitable for a continuous motion space while realizing low variance, and realizes the effect of learning while training. The scheme of the invention designs the continuous motion space with a heading angle limitationand uses 4 threads for parallel learning and training, so that compared with general deep reinforcement learning methods, the learning and training time is greatly improved, the sample correlation isreduced, the high utilization of exploration spaces and the diversity of exploration strategies are guaranteed, and thus the algorithm convergence, stability and the success rate of obstacle avoidance can be improved.

The invention relates to a color image encryption method based on an SHA-384 function, a spatiotemporal chaotic system, a quantum chaotic system and a neural network. The method includes the steps that an original color image I0 is calculated through the SHA-384 function, a Hash value is obtained as a secret key, the Hash value, a CML and one-dimension Logistic chaotic mapping are utilized for generating a chaos sequence, bit-level line-column scrambling is carried out on high four-digit images of components of three primary colors of the I0 through the chaos sequence, and a scrambled image I1 is obtained; the Logistic quantum chaotic system is utilized for generating a chaos sequence for encrypting the scrambled image, and is combined with the neural network to carry out parallel diffusion processing on all pixel values of components of three primary colors of the I1, and a final encrypted image I2 is obtained. By the method, the space of the secret key is greatly enlarged, the safety, encryption effect and secret key sensibility are higher, the attack resistance capacity is higher, the scrambling process and the encryption time are shorter, and hardware implementation is easier.

The invention discloses a robust mechanism research method of characteristic significance in image quality evaluation. The robust mechanism research method comprises the following steps: firstly, determining a target function of characteristic selection in the image quality evaluation, and initializing a model parameter; secondly, adding an optimal characteristic into a characteristic matrix, and removing a characteristic disturbance term; thirdly, calculating the significance of the characteristic selection in an image quality evaluation system; fourthly, judging whether the significance meets a system robust requirement or achieves an upper limit of a characteristic number; and finally, verifying a model classification effect. The characteristic significance is measured through an imported system characteristic signal to noise ratio, a constrained optimization problem of a smooth convex function in the image quality evaluation system is solved, interference on a classification face by non-significant characteristics is effectively lowered, the robustness of the image evaluation system is improved, and the self-adaptive optimization problem of characteristic attribute selection on the basis of an image quality evaluation network of a learning mechanism is solved.

The invention provides a computing unloading scheduling method based on depth reinforcement learning, which provides a method for computing unloading to make unloading decision for Internet of Thingsequipment, including making decisions on various aspects needing to be unloaded according to the basic model of computing unloading. Based on different optimization objectives, different optimizationobjectives can be achieved by changing the value function. TheDeep-SARSA algorithm is similar to DQN algorithm, which combines reinforcement learning and depth learning. It can effectively change theunloading state and unloading action into training samples of depth learning when cooperating with experience pool. The invention can effectively carry out machine learning on an unloading state modelof an unlimited dimension, reducing the complexity of learning, this method uses neural network as the linear approximator of Q value, which can effectively improve the training speed and reduce thesample required for training. This method can effectively make the best decision through deep reinforcement learning under the given model and optimization objective.