Abstract: One or more out-of-band input signals (GPIO) are handled and efficiently embedded into a USB capture stream. In order to conserve resources, the state of the input signals can be sent only when a change occurs. The signals are accurately time-stamped, and then presented within the context of the captured USB data. In order to provide maximum visibility, if the digital inputs occur during a normally filtered multi-packet sequence, the filter is canceled and the surrounding packets will also be sent to an analysis computer. Furthermore, because digital inputs may happen during a USB packet, the digital inputs are queued in a FIFO buffer until there is an opportunity to send the digital inputs. Even though the state of the inputs may be sent at a later time, the state of the inputs may be time-stamped when the state of the inputs is perceived by the analyzer.

Abstract: One or more out-of-band input signals (GPIO) are handled and efficiently embedded into a USB capture stream. In order to conserve resources, the state of the input signals can be sent only when a change occurs. The signals are accurately time-stamped, and then presented within the context of the captured USB data. In order to provide maximum visibility, if the digital inputs occur during a normally filtered multi-packet sequence, the filter is canceled and the surrounding packets will also be sent to an analysis computer. Furthermore, because digital inputs may happen during a USB packet, the digital inputs are queued in a FIFO buffer until there is an opportunity to send the digital inputs. Even though the state of the inputs may be sent at a later time, the state of the inputs may be time-stamped when the state of the inputs is perceived by the analyzer.

Abstract: One or more out-of-band input signals (GPIO) are handled and efficiently embedded into a USB capture stream. In order to conserve resources, the state of the input signals can be sent only when a change occurs. The signals are accurately time-stamped, and then presented within the context of the captured USB data. In order to provide maximum visibility, if the digital inputs occur during a normally filtered multi-packet sequence, the filter is canceled and the surrounding packets will also be sent to an analysis computer. Furthermore, because digital inputs may happen during a USB packet, the digital inputs are queued in a FIFO buffer until there is an opportunity to send the digital inputs. Even though the state of the inputs may be sent at a later time, the state of the inputs may be time-stamped when the state of the inputs is perceived by the analyzer.

Abstract: Split capture of USB protocol streams is disclosed. A first set of packets associated with a first USB protocol and a second set of packets associated with a second USB protocol are received at a hardware protocol analyzer via a monitored bus. The first set of packets and the second set of packets are maintained as separate streams at the hardware protocol analyzer. The first set of packets and the second set of packets are transferred from the hardware protocol analyzer to an analysis computer via a first logical connection configured to transfer packets comprising the first set of packets and a second logical connection configured to transfer packets comprising the second set of packets.

Abstract: A method is described for capturing USB data traffic for a monitored device by a USB analyzer using a single USB host controller. It comprises the steps of: generating and storing an address and communication speed associated with the USB analyzer; reading a USB packet; discarding selected read packets based on the stored analyzer address and communication speed; and transmitting the remaining packets to an analysis computer.

Abstract: A method is described for capturing USB data traffic for a monitored device by a USB analyzer using a single USB host controller. It comprises the steps of: generating and storing an address and communication speed associated with the USB analyzer; reading a USB packet; discarding selected read packets based on the stored analyzer address and communication speed; and transmitting the remaining packets to an analysis computer.

Abstract: A method is described for capturing USB data traffic for a monitored device by a USB analyzer using a single USB host controller. It comprises the steps of: generating and storing an address and communication speed associated with the USB analyzer; reading a USB packet; discarding selected read packets based on the stored analyzer address and communication speed; and transmitting the remaining packets to an analysis computer.

Abstract: The Universal Serial Bus (“USB”) 2.0 Specification defines three speeds of communication for its bus, and each has its own signaling characteristics. Due to the uniqueness of each speed, PHYs must be placed in a separate mode for each signaling rate. Although USB devices may know its communication speed, a general purpose USB analyzer must be able to analyze all USB communications. Rather than force the user to manually set the operating mode of the analyzer, this invention describes circuits for automatically and reliably determining the monitored USB communication speed.

Abstract: The Universal Serial Bus (“USB”) 2.0 Specification defines three speeds of communication for its bus, and each has its own signaling characteristics. Due to the uniqueness of each speed, PHYs must be placed in a separate mode for each signaling rate. Although USB devices may know its communication speed, a general purpose USB analyzer must be able to analyze all USB communications. Rather than force the user to manually set the operating mode of the analyzer, this invention describes circuits for automatically and reliably determining the monitored USB communication speed.

Abstract: A brain machine interface for decoding neural signals for control of a machine is provided. The brain machine interface estimates and then combines information from two classes of neural activity. A first estimator decodes movement plan information from neural signals representing plan activity. In one embodiment the first estimator includes an adaptive point-process filter or a maximum likelihood filter. A second estimator decodes peri-movement information from neural signals representing peri-movement activity. Each estimator is designed to estimate different aspects of movement such as movement goal variables or movement execution variables.

Abstract: A brain machine interface for decoding neural signals for control of a machine is provided. The brain machine interface estimates and then combines information from two classes of neural activity. A first estimator decodes movement plan information from neural signals representing plan activity. In one embodiment the first estimator includes an adaptive point-process filter or a maximum likelihood filter. A second estimator decodes peri-movement information from neural signals representing peri-movement activity. Each estimator is designed to estimate different aspects of movement such as movement goal variables or movement execution variables.