104 results about "Dynamic noise" patented technology

Homomorphic evaluations of functions are performed. The functions include operation(s). Variants of key switching and modulus switching are described and are performed prior to or after the operation(s). A key switching transformation converts a ciphertext with respect to a first secret key and a first modulus to a ciphertext with respect to a second secret key and a second modulus. A key switching transformation converts a first version of a ciphertext with respect to a first secret key and with some number r bits of precision to a second version of the selected ciphertext with respect to a second keys and with some other number r′ bits of precision. The ciphertexts may be operated on as polynomials represented using evaluation representation, which has benefits for multiplication and automorphism. Further, ciphertexts are associated with an estimate of noise, which is used to determine when to perform modulus switching on the ciphertexts.

A speech enhancement system improves the speech quality and intelligibility of a speech signal. The system includes a time-to-frequency converter that converts segments of a speech signal into frequency bands. A signal detector measures the signal power of the frequency bands of each speech segment. A background noise estimator measures a background noise detected in the speech signal. A dynamic noise reduction controller dynamically models the background noise in the speech signal. The speech enhancement renders a speech signal perceptually pleasing to a listener by dynamically attenuating a portion of the noise that occurs in a portion of the spectrum of the speech signal.

Provided are an apparatus and method for speech segment detection, and a system for speech recognition. The apparatus is equipped with a sound receiver and an image receiver and includes: a lip motion signal detector for detecting a motion region from image frames output from the image receiver, applying lip motion image feature information to the detected motion region, and detecting a lip motion signal; and a speech segment detector for detecting a speech segment using sound frames output from the sound receiver and the lip motion signal detected from the lip motion signal detector. Since lip motion image information is checked in a speech segment detection process, it is possible to prevent dynamic noise from being misrecognized as speech.

A semiconductor power network (100) decoupling capacitance (decap) budgeting problem is co-optimized with a wiring enhancement problem, wherein the solution is formulated to minimize the total decap to be added or wiring changes (addition of wires (420)) to be made to the network (100). Voltage constraints, available white space and other constraints determine the amount of decap to be added. Wire enhancements and / or added decap can be distributed throughout a violation region (120) of the semiconductor circuit (100) design to reduce dynamic supply voltage noise so that dynamic network voltages are at all times maintained greater than a user-specified threshold voltage level (220).

The invention provides a high-precision successive approximation type analog-digital converter and a performance lifting method based on a DNL (dynamic noise limiter). The high-precision successive approximation type analog-digital converter comprises a redundancy weight capacitor array, a comparator, a coding and reconstructing circuit, a weight storage circuit and a control logic circuit, wherein the redundancy weight capacitor array is used for acquiring an input voltage on a sampling stage to generate an output voltage, and realizing voltage addition and subtraction operation by controlling the corresponding weight capacitor of the redundancy weight capacitor array according to the comparator output results on the conversion stage; the comparator is used for comparing the output voltage of the redundancy weight capacitor array; the coding and reconstructing circuit is used for calculating an output code of the successive approximation type analog-digital converter according to the comparator output results and the capacitor weight in the weight storage circuit; the weight storage circuit is used for capacitor weight; the control logic circuit is used for controlling the sampling and conversion stage of the redundancy weight capacitor array. The invention further provides the performance lifting method based on the DNL (dynamic noise limiter). According to the high-precision successive approximation type analog-digital converter provided by the invention, the digital correction of capacitor mismatch errors is realized by adopting the capacitor array with the redundancy weight, and the conversion speed and the linear speed are increased.

A dynamic noise filter is disclosed, which includes a noise estimation circuit, a TNR filtering circuit, a SNR filtering circuit, a blending circuit and a motion estimation circuit. By performing noise estimation for each image, the invention dynamically adjusts the strengths of the TNR filter and the SNR filter as well as a blending ratio between the outputs of the TNR filter and the SNR filter, thereby obtaining the best image quality.

Homomorphic evaluation of a function is performed on input ciphertext(s), which were encrypted using a public key of an encryption scheme that also includes multiple secret keys. Each input ciphertext includes multiple real numbers that are kept with finite precision. Performing the homomorphic evaluation of the function includes performing operation(s). Performing each of one or more operations includes the following. A key-switching transformation is performed on selected ciphertext(s), including converting a first version of a selected ciphertext with respect to a first of the secret keys and with some number r bits of precision to a second version of the selected ciphertext with respect to a second of the secret keys and with some other number r′ bits of precision, r′>r. Each key switching transformation is performed prior to or after the operation(s) are evaluated. Results of the operation(s) are output.