Abstract: A method for unsupervised learning of one dimensional signals includes obtaining a sample vector from a one dimensional signal and storing the sample vector in a computer accessible memory (115) and identifying a higher dimension convex natural space where the surface of the function of a constant modulus (CM) performance measure of the sample vector is convex. The method further comprises transforming, with a computational processor (110), the sample vector from an original space into a higher dimension natural convex space CM matrix in the higher dimension natural convex space and solving, with a computational processor (110), for an optimum solution to the CM performance measure in the higher dimension convex natural space. The computational processor extracts an optimum solution to the CM performance measure in the original space.

Abstract: In one example, a projection capture system includes: a visible light projector to project a pattern on to a surface of a GUI control object placed on or above a work surface; a visible light camera to capture an image of the pattern projected on to the surface of the control object; and a controller operatively connected to the projector and the camera. Programming on the controller determines (1) a lateral position of the pattern relative to a reference position associated with the work surface based on the pattern image captured by the camera and (2) a height of the pattern above the work surface based on the lateral position of the pattern.

Abstract: In one example, a projection capture system includes: a visible light projector to project a pattern on to a surface of a GUI control object placed on or above a work surface; a visible light camera to capture an image of the pattern projected on to the surface of the control object; and a controller operatively connected to the projector and the camera. Programming on the controller determines (1) a lateral position of the pattern relative to a reference position associated with the work surface based on the pattern image captured by the camera and (2) a height the pattern above the work surface based on the lateral position of the pattern.

Abstract: A method for establishing a wireless, mobile-terminated data connection with a telematics-equipped vehicle so that data can be sent to and received from the vehicle. Generally, the method involves receiving network address update information from a wireless carrier system, using the network address update information to determine if a network address currently exists for a particular telematics-equipped vehicle, and using the current network address (if one exists) to establish a wireless, mobile-terminated data connection with the telematics-equipped vehicle. This method addresses some of the challenges involved in creating a mobile-terminated data connection with a device that has a temporary or dynamic network address.

Abstract: An improved mobile connectivity system and method allow for data transfers, such as related to service delivery, to and from mobile wireless units in an economical and secure manner. The system utilizes existing IP connectivity when available and otherwise determines an appropriate data exchange mechanism based on the length and security requirements of the intended exchange. Data exchange mechanisms include SMS, IP and other suitable protocols, and wireless carriers include cellular and non-cellular wireless carriers. In an example, each subscriber unit periodically, or when triggered, sends its location to a call center to allow the delivery of location-based services.

Abstract: An improved mobile connectivity system and method allow for data transfers, such as related to service delivery, to and from mobile wireless units in an economical and secure manner. The system utilizes existing IP connectivity when available and otherwise determines an appropriate data exchange mechanism based on the length and security requirements of the intended exchange. Data exchange mechanisms include SMS, IP and other suitable protocols, and wireless carriers include cellular and non-cellular wireless carriers. In an example, each subscriber unit periodically, or when triggered, sends its location to a call center to allow the delivery of location-based services.

Abstract: A method for establishing a wireless, mobile-terminated data connection with a telematics-equipped vehicle so that data can be sent to and received from the vehicle. Generally, the method involves receiving network address update information from a wireless carrier system, using the network address update information to determine if a network address currently exists for a particular telematics-equipped vehicle, and using the current network address (if one exists) to establish a wireless, mobile-terminated data connection with the telematics-equipped vehicle. This method addresses some of the challenges involved in creating a mobile-terminated data connection with a device that has a temporary or dynamic network address.

Abstract: A computer implemented method, system, and computer-readable medium for modifying and creating networked documents (105). To create a document (105), the method includes the acts of reading a control sheet (340), reading a content sheet (340), and generating the document (350, 360) using the control sheet (405) and the content sheet (407). To modify a document (105), the method includes the acts of reading a control sheet (405) having commands, reading a content sheet (407) having content (340), retrieving the document (105) using a command from the command sheet (350); and modifying the document using the control sheet (405) and the content sheet (350). The content sheet includes content of the document (105) and the control sheet (405) specifies the location of the content on the Web page. Either or both of the control sheet (405) and content sheet (407) may include print content.

Abstract: Communication channel characteristics are determined without the use of a training mode using a single-valued solution. A received signal xt is sent to an equalizer (508) which compensates for noise added to the received signal xt during transmission. To accurately determine the weights of the equalizer (508), the output of the equalizer (508) is transmitted to an amplitude square extractor (512) to generate a value representative of the amplitude of the received signal xt. Then, a forward-mapping module (516) maps the amplitude value from the n-dimensional space of the amplitude value to an augmented space having, in a preferred embodiment n2 dimensions. In the augmented space, an augmented space blind adaptation mechanism (520) is applied to generate a single-valued channel characteristic value in terms of an augmented space variable. Then, a backward-mapping module (524) is applied to generale the optimal weights for the equalizer (508) allowing an accurate recovery of the original signal st.

Abstract: The present invention is a computer-implemented method for calculating word accuracy. Word grouping accuracy values (260) are calculated (212) by using the character accuracy values (250) calculated by an OCR program present in a computer system. The present invention preferably uses these character accuracy values (250) to create a word grouping accuracy value (260). Various methods are employed to calculate the word accuracy (260), including binarizing the character accuracy values (250), modified averaging of the character accuracy values (250), and creating fuzzy visual displays of word grouping accuracy values (260). The calculated word grouping accuracy values (260) are then adjusted based upon known OCR strengths and weaknesses, and based upon comparisons to stored word lists and the application of language rules. In a system with multiple character recognition techniques, the system can compare the accuracy values (260) of different versions of the word groupings to find the most accurate version.

Abstract: An attribute extracting module (256) extracts attributes from a document (50) input into the system. An attribute comparison module (270) compares extracted attributes with multiple classes (54) of documents. Upon determining that attributes of the document (50) match attributes of one of the classes (54), the document (50) is classified as belonging to the class (54) and is processed in accordance with the system actions associated with the matched class (54). In one embodiment, attributes of the input document (50) are compared to the documents (56) belonging to the matched class (54) which are already on the system. If the system determines that the input document (50) matches one of the existing images (56), the user (240) is alerted that the input document (50) already exists in the system. In a further embodiment, a match is determined in response to a comparison quality measure determined by a quality assessment module (258). The comparison quality measure measures the accuracy of the comparison.

Abstract: Method and apparatus for separating touching characters within an optical character recognition (OCR) computer (1). An input document (20) is scanned by scanner (2), forming a set of scan line's (3). A segmentation process (4) is performed on the scan lines (3) to create a set of segmented image boxes (5). Candidate characters within the image boxes (5) are classified by a classification module (6), based upon a library of stored models (7). When the candidate characters have high degree of confidence, they are classified and coded into a binary form (8), such as ASCII. Those candidate characters that are not classified are processed by a touching character decision module (9) to determine whether a series of separation modules (10-14) is to be invoked. The execution of modules (10-13), followed by the reexecution of modules (4) and (6), may or may not cause all of the touching characters to be separated. Any touching characters that remain are subjected to one or more reprocessing cycles.