Abstract: The present disclosure generally relates to a method for authenticating a user using an electronic device, where the electronic device comprises a fingerprint sensor as well as a first and a second control unit. Preferably, the first control unit comprises a secure element and/or a secure block adapted to provide a secure processing environment. The present disclosure also relates to a corresponding electronic device and to a computer program product.

Abstract: The present disclosure generally relates to a method for authenticating a user using an electronic device, where the electronic device comprises a fingerprint sensor as well as a first and a second control unit. Preferably, the first control unit comprises a secure element and/or a secure block adapted to provide a secure processing environment. The present disclosure also relates to a corresponding electronic device and to a computer program product.

Abstract: The present invention generally relates to a method for removing disturbances in an image captured by a fingerprint sensor, and specifically to reduction of noise in an acquired fingerprint image by incorporating the sensing principle into the applied method for noise reduction, wherein the noise reduced image is used for determining a representation of a fingerprint pattern. Advantages with the invention include enhanced determination of fingerprint patterns from fingerprint images captured using a fingerprint sensor. The invention also relates to a corresponding electronic device and to a computer program product.

Abstract: The present invention generally relates to a method for removing disturbances in an image captured by a fingerprint sensor, and specifically to reduction of noise in an acquired fingerprint image by incorporating the sensing principle into the applied method for noise reduction, wherein the noise reduced image is used for determining a representation of a fingerprint pattern. Advantages with the invention include enhanced determination of fingerprint patterns from fingerprint images captured using a fingerprint sensor. The invention also relates to a corresponding electronic device and to a computer program product.

Abstract: The present invention generally relates to a method for removing disturbances in an image captured by a fingerprint sensor, and specifically to reduction of noise in an acquired fingerprint image by incorporating the sensing principle into the applied method for noise reduction, wherein the noise reduced image is used for determining a representation of a fingerprint pattern. Advantages with the invention include enhanced determination of fingerprint patterns from fingerprint images captured using a fingerprint sensor. The invention also relates to a corresponding electronic device and to a computer program product.

Abstract: The present invention generally relates to a method for removing disturbances in an image captured by a fingerprint sensor, and specifically to reduction of noise in an acquired fingerprint image by incorporating the sensing principle into the applied method for noise reduction, wherein the noise reduced image is used for determining a representation of a fingerprint pattern. Advantages with the invention include enhanced determination of fingerprint patterns from fingerprint images captured using a fingerprint sensor. The invention also relates to a corresponding electronic device and to a computer program product.

Abstract: Linear symbol level equalisation is used to estimate a transmitted symbol vector xn(0) in an nth observation window yn of signals received from multiple users each using a different spreading code. An iterative conjugate gradient algorithm resolves a column vector z that satisfies Az=b, A being a square matrix and b being a column vector. The matrix vector product Apk used in each respective kth iteration of the algorithm is computed using at least one fast transform. The receiver or detector estimates a posterior mean {circumflex over (x)}LMMSE,n(0) from the computed column vector z, then utilises the estimated posterior mean to determine the transmitted symbol vector xn(0). The posterior mean {circumflex over (x)}LMMSE,n(0) may be estimated from matrix A and vector b. Different examples have the square matrix A with an inner or an outer product form; and have the fast transform as a fast Walsh-Hadamard transform and/or a fast (inverse) Fourier transform.

Abstract: Linear symbol level equalisation is used to estimate a transmitted symbol vector xn(0) in an nth observation window yn of signals received from multiple users each using a different spreading code. An iterative conjugate gradient algorithm resolves a column vector z that satisfies Az=b, A being a square matrix and b being a column vector. The matrix vector product Apk used in each respective kth iteration of the algorithm is computed using at least one fast transform. The receiver or detector estimates a posterior mean {circumflex over (x)}LMMSE,n(0) from the computed column vector z, then utilises the estimated posterior mean to determine the transmitted symbol vector xn(0). The posterior mean {circumflex over (x)}LMMSE,n(0) may be estimated from matrix A and vector b. Different examples have the square matrix A with an inner or an outer product form; and have the fast transform as a fast Walsh-Hadamard transform and/or a fast (inverse) Fourier transform.

Abstract: Exemplary embodiments of the invention provide a generalized Turbo principle that enables the exchange of region beliefs between components. The generalized Turbo principle provides various advantages over the traditional Turbo principle such as, for example, a lower Bit Error Rate (BER) and/or a better quality of the end-result marginals. In one exemplary embodiment, a method includes: receiving an encoded signal (501); and decoding the received signal using a generalized Turbo principle wherein region beliefs are exchanged between components (502). In another exemplary embodiment, methods, computer programs and apparatus are presented for generating a graph structure for a system having a plurality of components. As a non-limiting example, the generated graph structure may be seen to correspond to the region graphs underlying the generalized Turbo principle.